Publish validated Clover Image Tiny research preview

.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+assets/clover-image-tiny-local-mps-library-seed-1469.png filter=lfs diff=lfs merge=lfs -text
+assets/clover-image-tiny-paired-contact-sheet.png filter=lfs diff=lfs merge=lfs -text

DATA_PROVENANCE.md

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+# Data Provenance — Clover Image Tiny Research Preview
+
+This document records the portable data identity for the exact Stage B
+calibration checkpoint in this package. It deliberately contains no local
+machine paths, private storage locations, or source-image payloads.
+
+## Clover fine-tuning corpus
+
+| Field | Value |
+|---|---|
+| Dataset | `Spawning/PD3M` |
+| Pinned revision | `2a5eb24a8dccf245acd8e56341761aee06da0bdf` |
+| Accepted records | 1,000 image-caption pairs |
+| Split | 973 train / 17 validation / 10 test |
+| Shards | 1 deterministic checksummed shard |
+| Dataset gate license | `CDLA-Permissive-2.0` |
+| Item status | CC0-1.0 or Public Domain Mark 1.0, recorded per item |
+| Manifest SHA-256 | `50c1249f1cb0d8d690a9acc451ca10c9432eb5a7f4e26f34acb5462096e72322` |
+| Preprocessing version | `clover-pd3m-center-crop-512-jpeg95-v1` |
+
+Every accepted manifest row records a stable item ID, caption, split, source
+organization and URL, item-level status, source MD5, transformed SHA-256,
+original dimensions and MIME type, crop/resize details, filtering result, and
+removal status. Preprocessing applies EXIF transpose, a deterministic square
+center crop, Lanczos resize to 512×512, and JPEG encoding with stripped
+metadata, quality 95, and subsampling 0.
+
+The captions paired with these accepted items were used as the Stage B training
+text. They are not represented as a separate, untracked prompt corpus. Neither
+the source images nor the gated training shard is distributed in this model
+package.
+
+## Checkpoint binding
+
+The data identity above is bound to:
+
+- experiment `clover-kd-20260712T050925Z-01KXABNHP0`;
+- optimizer step 500, microstep 4,000, sample position 4,000;
+- checkpoint SHA-256
+  `4a5b99ff18478742528a0d31c97dcee939b166a51be858721d40ad5984110893`;
+- checkpoint-bundle SHA-256
+  `384b6515f5f26838aea33ec9a941e06610a20764f0b8637c8b7b0667bfc0d447`;
+- resolved-config SHA-256
+  `80cf9395d1f587dc0c1d440d9f5b55c55c20703187998509bb306d19d463f597`.
+
+The bundle digest includes checkpoint metadata in addition to the format-2
+resume artifacts, preventing the data identity from being relabeled without
+changing the approved bundle identity.
+
+## Engineering gallery prompts
+
+The bundled paired contact sheet uses eight fixed project-authored prompts from
+the 256-prompt `clover-eval-v1` suite. It is evaluation input, not training
+data. Each row fixes the prompt and seed and compares the pinned starting model
+on the left with this Stage B checkpoint on the right. The contact sheet
+SHA-256 is
+`8653d1105b7b0c56e2385a127336dbe9b3a1a03c8518edb4934353a9d8e13bfa`.
+
+This subset checks that the pipeline produces finite, nonblank images. It does
+not establish representative quality, prompt alignment, diversity, fairness,
+or human preference.
+
+## Foundational upstream provenance limitation
+
+The 1,000-pair manifest fully describes only the additional Clover calibration
+data. It does not replace or erase the pretraining lineage already embedded in
+the starting student and frozen teacher.
+
+The pinned BK-SDM-Tiny-2M model card names LAION-Aesthetics V2 6.25+ and
+2,256,472 pairs, but does not supply the per-record license and provenance
+evidence required by Clover's full release policy. Complete per-record
+provenance for all foundational data behind the upstream student and teacher is
+therefore not available to this project. The upstream checkpoints and their
+declared CreativeML OpenRAIL-M licenses are pinned and disclosed, but that is
+not equivalent to a complete foundational dataset audit.
+
+This inherited limitation is material. The weights are distributed only as a
+**RESEARCH PREVIEW · PRODUCTION PILOT · NOT RELEASE-READY** artifact.

LICENSE

@@ -0,0 +1,82 @@
+Copyright (c) 2022 Robin Rombach and Patrick Esser and contributors
+
+CreativeML Open RAIL-M
+dated August 22, 2022
+
+Section I: PREAMBLE
+
+Multimodal generative models are being widely adopted and used, and have the potential to transform the way artists, among other individuals, conceive and benefit from AI or ML technologies as a tool for content creation.
+
+Notwithstanding the current and potential benefits that these artifacts can bring to society at large, there are also concerns about potential misuses of them, either due to their technical limitations or ethical considerations.
+
+In short, this license strives for both the open and responsible downstream use of the accompanying model. When it comes to the open character, we took inspiration from open source permissive licenses regarding the grant of IP rights. Referring to the downstream responsible use, we added use-based restrictions not permitting the use of the Model in very specific scenarios, in order for the licensor to be able to enforce the license in case potential misuses of the Model may occur. At the same time, we strive to promote open and responsible research on generative models for art and content generation.
+
+Even though downstream derivative versions of the model could be released under different licensing terms, the latter will always have to include - at minimum - the same use-based restrictions as the ones in the original license (this license). We believe in the intersection between open and responsible AI development; thus, this License aims to strike a balance between both in order to enable responsible open-science in the field of AI.
+
+This License governs the use of the model (and its derivatives) and is informed by the model card associated with the model.
+
+NOW THEREFORE, You and Licensor agree as follows:
+
+1. Definitions
+
+- "License" means the terms and conditions for use, reproduction, and Distribution as defined in this document.
+- "Data" means a collection of information and/or content extracted from the dataset used with the Model, including to train, pretrain, or otherwise evaluate the Model. The Data is not licensed under this License.
+- "Output" means the results of operating a Model as embodied in informational content resulting therefrom.
+- "Model" means any accompanying machine-learning based assemblies (including checkpoints), consisting of learnt weights, parameters (including optimizer states), corresponding to the model architecture as embodied in the Complementary Material, that have been trained or tuned, in whole or in part on the Data, using the Complementary Material.
+- "Derivatives of the Model" means all modifications to the Model, works based on the Model, or any other model which is created or initialized by transfer of patterns of the weights, parameters, activations or output of the Model, to the other model, in order to cause the other model to perform similarly to the Model, including - but not limited to - distillation methods entailing the use of intermediate data representations or methods based on the generation of synthetic data by the Model for training the other model.
+- "Complementary Material" means the accompanying source code and scripts used to define, run, load, benchmark or evaluate the Model, and used to prepare data for training or evaluation, if any. This includes any accompanying documentation, tutorials, examples, etc, if any.
+- "Distribution" means any transmission, reproduction, publication or other sharing of the Model or Derivatives of the Model to a third party, including providing the Model as a hosted service made available by electronic or other remote means - e.g. API-based or web access.
+- "Licensor" means the copyright owner or entity authorized by the copyright owner that is granting the License, including the persons or entities that may have rights in the Model and/or distributing the Model.
+- "You" (or "Your") means an individual or Legal Entity exercising permissions granted by this License and/or making use of the Model for whichever purpose and in any field of use, including usage of the Model in an end-use application - e.g. chatbot, translator, image generator.
+- "Third Parties" means individuals or legal entities that are not under common control with Licensor or You.
+- "Contribution" means any work of authorship, including the original version of the Model and any modifications or additions to that Model or Derivatives of the Model thereof, that is intentionally submitted to Licensor for inclusion in the Model by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, "submitted" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Model, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as "Not a Contribution."
+- "Contributor" means Licensor and any individual or Legal Entity on behalf of whom a Contribution has been received by Licensor and subsequently incorporated within the Model.
+
+Section II: INTELLECTUAL PROPERTY RIGHTS
+
+Both copyright and patent grants apply to the Model, Derivatives of the Model and Complementary Material. The Model and Derivatives of the Model are subject to additional terms as described in Section III.
+
+2. Grant of Copyright License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare, publicly display, publicly perform, sublicense, and distribute the Complementary Material, the Model, and Derivatives of the Model.
+3. Grant of Patent License. Subject to the terms and conditions of this License and where and as applicable, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this paragraph) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Model and the Complementary Material, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Model to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Model and/or Complementary Material or a Contribution incorporated within the Model and/or Complementary Material constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for the Model and/or Work shall terminate as of the date such litigation is asserted or filed.
+
+Section III: CONDITIONS OF USAGE, DISTRIBUTION AND REDISTRIBUTION
+
+4. Distribution and Redistribution. You may host for Third Party remote access purposes (e.g. software-as-a-service), reproduce and distribute copies of the Model or Derivatives of the Model thereof in any medium, with or without modifications, provided that You meet the following conditions:
+Use-based restrictions as referenced in paragraph 5 MUST be included as an enforceable provision by You in any type of legal agreement (e.g. a license) governing the use and/or distribution of the Model or Derivatives of the Model, and You shall give notice to subsequent users You Distribute to, that the Model or Derivatives of the Model are subject to paragraph 5. This provision does not apply to the use of Complementary Material.
+You must give any Third Party recipients of the Model or Derivatives of the Model a copy of this License;
+You must cause any modified files to carry prominent notices stating that You changed the files;
+You must retain all copyright, patent, trademark, and attribution notices excluding those notices that do not pertain to any part of the Model, Derivatives of the Model.
+You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions - respecting paragraph 4.a. - for use, reproduction, or Distribution of Your modifications, or for any such Derivatives of the Model as a whole, provided Your use, reproduction, and Distribution of the Model otherwise complies with the conditions stated in this License.
+5. Use-based restrictions. The restrictions set forth in Attachment A are considered Use-based restrictions. Therefore You cannot use the Model and the Derivatives of the Model for the specified restricted uses. You may use the Model subject to this License, including only for lawful purposes and in accordance with the License. Use may include creating any content with, finetuning, updating, running, training, evaluating and/or reparametrizing the Model. You shall require all of Your users who use the Model or a Derivative of the Model to comply with the terms of this paragraph (paragraph 5).
+6. The Output You Generate. Except as set forth herein, Licensor claims no rights in the Output You generate using the Model. You are accountable for the Output you generate and its subsequent uses. No use of the output can contravene any provision as stated in the License.
+
+Section IV: OTHER PROVISIONS
+
+7. Updates and Runtime Restrictions. To the maximum extent permitted by law, Licensor reserves the right to restrict (remotely or otherwise) usage of the Model in violation of this License, update the Model through electronic means, or modify the Output of the Model based on updates. You shall undertake reasonable efforts to use the latest version of the Model.
+8. Trademarks and related. Nothing in this License permits You to make use of Licensors’ trademarks, trade names, logos or to otherwise suggest endorsement or misrepresent the relationship between the parties; and any rights not expressly granted herein are reserved by the Licensors.
+9. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Model and the Complementary Material (and each Contributor provides its Contributions) on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Model, Derivatives of the Model, and the Complementary Material and assume any risks associated with Your exercise of permissions under this License.
+10. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Model and the Complementary Material (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages.
+11. Accepting Warranty or Additional Liability. While redistributing the Model, Derivatives of the Model and the Complementary Material thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability.
+12. If any provision of this License is held to be invalid, illegal or unenforceable, the remaining provisions shall be unaffected thereby and remain valid as if such provision had not been set forth herein.
+
+END OF TERMS AND CONDITIONS
+
+
+
+
+Attachment A
+
+Use Restrictions
+
+You agree not to use the Model or Derivatives of the Model:
+- In any way that violates any applicable national, federal, state, local or international law or regulation;
+- For the purpose of exploiting, harming or attempting to exploit or harm minors in any way;
+- To generate or disseminate verifiably false information and/or content with the purpose of harming others;
+- To generate or disseminate personal identifiable information that can be used to harm an individual;
+- To defame, disparage or otherwise harass others;
+- For fully automated decision making that adversely impacts an individual’s legal rights or otherwise creates or modifies a binding, enforceable obligation;
+- For any use intended to or which has the effect of discriminating against or harming individuals or groups based on online or offline social behavior or known or predicted personal or personality characteristics;
+- To exploit any of the vulnerabilities of a specific group of persons based on their age, social, physical or mental characteristics, in order to materially distort the behavior of a person pertaining to that group in a manner that causes or is likely to cause that person or another person physical or psychological harm;
+- For any use intended to or which has the effect of discriminating against individuals or groups based on legally protected characteristics or categories;
+- To provide medical advice and medical results interpretation;
+- To generate or disseminate information for the purpose to be used for administration of justice, law enforcement, immigration or asylum processes, such as predicting an individual will commit fraud/crime commitment (e.g. by text profiling, drawing causal relationships between assertions made in documents, indiscriminate and arbitrarily-targeted use).

LICENSE-CODE

@@ -0,0 +1,165 @@
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+   1. Definitions.
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+   institute patent litigation against any entity (including a
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+   any Contribution intentionally submitted for inclusion in the Work
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+
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+   whether in tort (including negligence), contract, or otherwise,
+   unless required by applicable law (such as deliberate and grossly
+   negligent acts) or agreed to in writing, shall any Contributor be
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+   incidental, or consequential damages of any character arising as a
+   result of this License or out of the use or inability to use the
+   Work (including but not limited to damages for loss of goodwill,
+   work stoppage, computer failure or malfunction, or any and all
+   other commercial damages or losses), even if such Contributor
+   has been advised of the possibility of such damages.
+
+   9. Accepting Warranty or Additional Liability. While redistributing
+   the Work or Derivative Works thereof, You may choose to offer,
+   and charge a fee for, acceptance of support, warranty, indemnity,
+   or other liability obligations and/or rights consistent with this
+   License. However, in accepting such obligations, You may act only
+   on Your own behalf and on Your sole responsibility, not on behalf
+   of any other Contributor, and only if You agree to indemnify,
+   defend, and hold each Contributor harmless for any liability
+   incurred by, or claims asserted against, such Contributor by reason
+   of your accepting any such warranty or additional liability.
+
+   END OF TERMS AND CONDITIONS
+

LICENSE-MODEL-CREATIVEML-OPENRAIL-M.txt

@@ -0,0 +1,82 @@
+Copyright (c) 2022 Robin Rombach and Patrick Esser and contributors
+
+CreativeML Open RAIL-M
+dated August 22, 2022
+
+Section I: PREAMBLE
+
+Multimodal generative models are being widely adopted and used, and have the potential to transform the way artists, among other individuals, conceive and benefit from AI or ML technologies as a tool for content creation.
+
+Notwithstanding the current and potential benefits that these artifacts can bring to society at large, there are also concerns about potential misuses of them, either due to their technical limitations or ethical considerations.
+
+In short, this license strives for both the open and responsible downstream use of the accompanying model. When it comes to the open character, we took inspiration from open source permissive licenses regarding the grant of IP rights. Referring to the downstream responsible use, we added use-based restrictions not permitting the use of the Model in very specific scenarios, in order for the licensor to be able to enforce the license in case potential misuses of the Model may occur. At the same time, we strive to promote open and responsible research on generative models for art and content generation.
+
+Even though downstream derivative versions of the model could be released under different licensing terms, the latter will always have to include - at minimum - the same use-based restrictions as the ones in the original license (this license). We believe in the intersection between open and responsible AI development; thus, this License aims to strike a balance between both in order to enable responsible open-science in the field of AI.
+
+This License governs the use of the model (and its derivatives) and is informed by the model card associated with the model.
+
+NOW THEREFORE, You and Licensor agree as follows:
+
+1. Definitions
+
+- "License" means the terms and conditions for use, reproduction, and Distribution as defined in this document.
+- "Data" means a collection of information and/or content extracted from the dataset used with the Model, including to train, pretrain, or otherwise evaluate the Model. The Data is not licensed under this License.
+- "Output" means the results of operating a Model as embodied in informational content resulting therefrom.
+- "Model" means any accompanying machine-learning based assemblies (including checkpoints), consisting of learnt weights, parameters (including optimizer states), corresponding to the model architecture as embodied in the Complementary Material, that have been trained or tuned, in whole or in part on the Data, using the Complementary Material.
+- "Derivatives of the Model" means all modifications to the Model, works based on the Model, or any other model which is created or initialized by transfer of patterns of the weights, parameters, activations or output of the Model, to the other model, in order to cause the other model to perform similarly to the Model, including - but not limited to - distillation methods entailing the use of intermediate data representations or methods based on the generation of synthetic data by the Model for training the other model.
+- "Complementary Material" means the accompanying source code and scripts used to define, run, load, benchmark or evaluate the Model, and used to prepare data for training or evaluation, if any. This includes any accompanying documentation, tutorials, examples, etc, if any.
+- "Distribution" means any transmission, reproduction, publication or other sharing of the Model or Derivatives of the Model to a third party, including providing the Model as a hosted service made available by electronic or other remote means - e.g. API-based or web access.
+- "Licensor" means the copyright owner or entity authorized by the copyright owner that is granting the License, including the persons or entities that may have rights in the Model and/or distributing the Model.
+- "You" (or "Your") means an individual or Legal Entity exercising permissions granted by this License and/or making use of the Model for whichever purpose and in any field of use, including usage of the Model in an end-use application - e.g. chatbot, translator, image generator.
+- "Third Parties" means individuals or legal entities that are not under common control with Licensor or You.
+- "Contribution" means any work of authorship, including the original version of the Model and any modifications or additions to that Model or Derivatives of the Model thereof, that is intentionally submitted to Licensor for inclusion in the Model by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, "submitted" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Model, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as "Not a Contribution."
+- "Contributor" means Licensor and any individual or Legal Entity on behalf of whom a Contribution has been received by Licensor and subsequently incorporated within the Model.
+
+Section II: INTELLECTUAL PROPERTY RIGHTS
+
+Both copyright and patent grants apply to the Model, Derivatives of the Model and Complementary Material. The Model and Derivatives of the Model are subject to additional terms as described in Section III.
+
+2. Grant of Copyright License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare, publicly display, publicly perform, sublicense, and distribute the Complementary Material, the Model, and Derivatives of the Model.
+3. Grant of Patent License. Subject to the terms and conditions of this License and where and as applicable, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this paragraph) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Model and the Complementary Material, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Model to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Model and/or Complementary Material or a Contribution incorporated within the Model and/or Complementary Material constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for the Model and/or Work shall terminate as of the date such litigation is asserted or filed.
+
+Section III: CONDITIONS OF USAGE, DISTRIBUTION AND REDISTRIBUTION
+
+4. Distribution and Redistribution. You may host for Third Party remote access purposes (e.g. software-as-a-service), reproduce and distribute copies of the Model or Derivatives of the Model thereof in any medium, with or without modifications, provided that You meet the following conditions:
+Use-based restrictions as referenced in paragraph 5 MUST be included as an enforceable provision by You in any type of legal agreement (e.g. a license) governing the use and/or distribution of the Model or Derivatives of the Model, and You shall give notice to subsequent users You Distribute to, that the Model or Derivatives of the Model are subject to paragraph 5. This provision does not apply to the use of Complementary Material.
+You must give any Third Party recipients of the Model or Derivatives of the Model a copy of this License;
+You must cause any modified files to carry prominent notices stating that You changed the files;
+You must retain all copyright, patent, trademark, and attribution notices excluding those notices that do not pertain to any part of the Model, Derivatives of the Model.
+You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions - respecting paragraph 4.a. - for use, reproduction, or Distribution of Your modifications, or for any such Derivatives of the Model as a whole, provided Your use, reproduction, and Distribution of the Model otherwise complies with the conditions stated in this License.
+5. Use-based restrictions. The restrictions set forth in Attachment A are considered Use-based restrictions. Therefore You cannot use the Model and the Derivatives of the Model for the specified restricted uses. You may use the Model subject to this License, including only for lawful purposes and in accordance with the License. Use may include creating any content with, finetuning, updating, running, training, evaluating and/or reparametrizing the Model. You shall require all of Your users who use the Model or a Derivative of the Model to comply with the terms of this paragraph (paragraph 5).
+6. The Output You Generate. Except as set forth herein, Licensor claims no rights in the Output You generate using the Model. You are accountable for the Output you generate and its subsequent uses. No use of the output can contravene any provision as stated in the License.
+
+Section IV: OTHER PROVISIONS
+
+7. Updates and Runtime Restrictions. To the maximum extent permitted by law, Licensor reserves the right to restrict (remotely or otherwise) usage of the Model in violation of this License, update the Model through electronic means, or modify the Output of the Model based on updates. You shall undertake reasonable efforts to use the latest version of the Model.
+8. Trademarks and related. Nothing in this License permits You to make use of Licensors’ trademarks, trade names, logos or to otherwise suggest endorsement or misrepresent the relationship between the parties; and any rights not expressly granted herein are reserved by the Licensors.
+9. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Model and the Complementary Material (and each Contributor provides its Contributions) on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Model, Derivatives of the Model, and the Complementary Material and assume any risks associated with Your exercise of permissions under this License.
+10. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Model and the Complementary Material (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages.
+11. Accepting Warranty or Additional Liability. While redistributing the Model, Derivatives of the Model and the Complementary Material thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability.
+12. If any provision of this License is held to be invalid, illegal or unenforceable, the remaining provisions shall be unaffected thereby and remain valid as if such provision had not been set forth herein.
+
+END OF TERMS AND CONDITIONS
+
+
+
+
+Attachment A
+
+Use Restrictions
+
+You agree not to use the Model or Derivatives of the Model:
+- In any way that violates any applicable national, federal, state, local or international law or regulation;
+- For the purpose of exploiting, harming or attempting to exploit or harm minors in any way;
+- To generate or disseminate verifiably false information and/or content with the purpose of harming others;
+- To generate or disseminate personal identifiable information that can be used to harm an individual;
+- To defame, disparage or otherwise harass others;
+- For fully automated decision making that adversely impacts an individual’s legal rights or otherwise creates or modifies a binding, enforceable obligation;
+- For any use intended to or which has the effect of discriminating against or harming individuals or groups based on online or offline social behavior or known or predicted personal or personality characteristics;
+- To exploit any of the vulnerabilities of a specific group of persons based on their age, social, physical or mental characteristics, in order to materially distort the behavior of a person pertaining to that group in a manner that causes or is likely to cause that person or another person physical or psychological harm;
+- For any use intended to or which has the effect of discriminating against individuals or groups based on legally protected characteristics or categories;
+- To provide medical advice and medical results interpretation;
+- To generate or disseminate information for the purpose to be used for administration of justice, law enforcement, immigration or asylum processes, such as predicting an individual will commit fraud/crime commitment (e.g. by text profiling, drawing causal relationships between assertions made in documents, indiscriminate and arbitrarily-targeted use).

MODEL_DATA_LICENSES.md

@@ -0,0 +1,57 @@
+# Model and Data Licenses — Clover Image Tiny Research Preview
+
+This is a conservative license and provenance ledger for the exact research
+preview. The complete bundled license texts control over this summary. This is
+not legal advice.
+
+| Component | Exact identity | License/status | Consequence |
+|---|---|---|---|
+| Preview model weights | Stage B step 500; checkpoint `4a5b99ff18478742528a0d31c97dcee939b166a51be858721d40ad5984110893` | CreativeML OpenRAIL-M derivative | Retain the complete terms, attribution, modification notice, and use restrictions |
+| Starting student | `nota-ai/bk-sdm-tiny-2m@aad3e0e8ba61b7cb9f64869dc4e586f8ad9d3665` | Pinned model card declares CreativeML OpenRAIL-M | Derivative-weight obligations apply |
+| Frozen teacher | `CompVis/stable-diffusion-v1-4@133a221b8aa7292a167afc5127cb63fb5005638b` | Pinned model card declares CreativeML OpenRAIL-M | Distillation from outputs and activations retains derivative-weight obligations |
+| Tokenizer and text encoder | Byte-identical components in the two pinned pipelines | CreativeML OpenRAIL-M lineage | Bundled as upstream model components |
+| VAE | Byte-identical component in the two pinned pipelines | CreativeML OpenRAIL-M lineage | Bundled as an upstream model component |
+| Clover fine-tuning data | `Spawning/PD3M@2a5eb24a8dccf245acd8e56341761aee06da0bdf`; manifest `50c1249f1cb0d8d690a9acc451ca10c9432eb5a7f4e26f34acb5462096e72322` | Dataset declaration: CDLA-Permissive-2.0; accepted items: CC0-1.0 or Public Domain Mark 1.0 | Dataset and item terms remain separate from the model license; raw data is not bundled |
+| Calibration captions | Captions paired with the exact accepted PD3M items | Same recorded item/dataset lineage | Not a separate untracked training corpus |
+| Example and packaging code | Files authored by the Clover-Image project | Apache-2.0 | Code license does not relicense model weights or data |
+| Runtime dependencies | Pinned packages listed in `requirements.txt` | Their own upstream licenses | Installed separately; no dependency is relicensed by this package |
+
+## Weight-license selection
+
+Both pinned upstream weight repositories declare CreativeML OpenRAIL-M. The
+Stage B process modified the starting BK-SDM-Tiny-2M weights using task/output
+and feature distillation from the frozen Stable Diffusion v1.4 teacher plus the
+licensed calibration corpus. The resulting weights are therefore labeled as a
+CreativeML OpenRAIL-M derivative rather than Apache-2.0.
+
+The bundled canonical CreativeML OpenRAIL-M file is 14,385 bytes with SHA-256
+`be351ebe7ac01bcdbb018639aadcfd38f136b7dc3f2a3d4d3a24db51d1b210ef`.
+The separately bundled Apache-2.0 project-code license is 9,147 bytes with
+SHA-256
+`e26a0375b714267325c27905ba947fdc41ebc0b7a36940a49ae12379ed6208d6`.
+
+Calling this artifact a research preview does not create a new weight license
+or waive OpenRAIL-M restrictions. Users must review and follow the complete
+terms for copying, redistribution, modification, and use.
+
+## Data terms
+
+The fine-tuning dataset gate is `CDLA-Permissive-2.0`, while each accepted item
+retains its recorded CC0-1.0 declaration or Public Domain Mark 1.0 status.
+Neither the model-weight license nor the project-code license replaces those
+data terms. Source images and the gated training shard are not redistributed in
+this package.
+
+## Known unresolved provenance scope
+
+The Clover calibration set has an exact 1,000-row manifest. The upstream
+foundational data does not have equivalent per-record evidence in this project.
+The pinned BK-SDM model card identifies LAION-Aesthetics V2 6.25+ and 2,256,472
+pairs, but not the item-level evidence demanded by Clover's full release policy.
+The project likewise does not claim a complete per-record audit of every
+foundational example behind the upstream teacher.
+
+Pinned model IDs, revisions, and license declarations are evidence of weight
+lineage; they are not substitutes for foundational data provenance. This
+unresolved inherited scope is a principal reason the package remains
+**RESEARCH PREVIEW · PRODUCTION PILOT · NOT RELEASE-READY**.

README.md

@@ -0,0 +1,194 @@
+---
+library_name: diffusers
+pipeline_tag: text-to-image
+inference: false
+base_model: nota-ai/bk-sdm-tiny-2m
+license: creativeml-openrail-m
+tags:
+  - text-to-image
+  - diffusion
+  - stable-diffusion
+  - knowledge-distillation
+  - research-preview
+---
+
+# Clover Image Tiny — Research Preview
+
+This is **Clover Image Tiny**, an early conventional knowledge-distillation
+checkpoint released as a research preview. It is a production-data pilot, not
+a release-ready model. It uses the compact BK-SDM-Tiny-2M architecture, a
+conventional 50-step PNDM schedule, 512×512 output, and classifier-free
+guidance 7.5.
+
+The checkpoint is useful for inspecting an early, licensed-data quality-refresh
+experiment. It is not a finished Clover release, a quality benchmark, or a
+claim of uniformly better output than its starting model.
+
+## Exact artifact identity
+
+| Field | Value |
+|---|---|
+| Repository | `neonforestmist/Clover-Image-Tiny` |
+| Status | **RESEARCH PREVIEW · PRODUCTION PILOT · NOT RELEASE-READY** |
+| Experiment | `clover-kd-20260712T050925Z-01KXABNHP0` |
+| Training stage | Stage B knowledge distillation |
+| Optimizer step | 500 |
+| Checkpoint SHA-256 | `4a5b99ff18478742528a0d31c97dcee939b166a51be858721d40ad5984110893` |
+| Checkpoint-bundle SHA-256 | `384b6515f5f26838aea33ec9a941e06610a20764f0b8637c8b7b0667bfc0d447` |
+| Resolved-config SHA-256 | `80cf9395d1f587dc0c1d440d9f5b55c55c20703187998509bb306d19d463f597` |
+| Dataset-manifest SHA-256 | `50c1249f1cb0d8d690a9acc451ca10c9432eb5a7f4e26f34acb5462096e72322` |
+| Package bytes | `1671489892` |
+| Package files | `30` |
+| Validated Stage B source-package checksums SHA-256 | `d9a28d5fe6f5b675ee1b9db52e6d0493c8d3d357bb824eac590911acbd5c3ebc` |
+| Builder source commit | `1880c3eb55133e8b7b1786ddea8e732d16a2f902` |
+
+The checkpoint completed 500 optimizer steps, 4,000 microsteps, and 4,000
+sample presentations. All 500 recorded training rows were finite and had a
+nonzero gradient. Those are training-integrity observations, not image-quality
+scores.
+
+## Example gallery
+
+![Eight paired baseline and Clover Image Tiny examples](assets/clover-image-tiny-paired-contact-sheet.png)
+
+Each row uses the same prompt and seed. The **left column is the pinned
+BK-SDM-Tiny-2M baseline; only the right column is this Stage B checkpoint**.
+The gallery was generated on an NVIDIA L4 in bfloat16 with 50 PNDM steps,
+guidance 7.5, an empty negative prompt, and 512×512 output.
+With the pinned Diffusers 0.39.0 scheduler, those 50 requested PNDM steps use
+51 U-Net invocations because PLMS repeats its first retained timestep.
+
+All eight Stage B gallery images were finite, nonblank, nonblack, and returned
+clear from the packaged upstream safety checker in that measured run. This
+small engineering subset is not a general safety or quality evaluation. The
+changes are modest and not uniformly better: the bottle example loses prompt
+fidelity, hands remain weak, and some details change without clear improvement.
+
+## Run with Diffusers
+
+Install the pinned preview environment:
+
+```bash
+python -m pip install -r requirements.txt
+```
+
+Then generate with the conventional configuration used for the gallery:
+
+```python
+import torch
+from diffusers import DiffusionPipeline, PNDMScheduler
+
+model_id = "neonforestmist/Clover-Image-Tiny"
+if torch.cuda.is_available():
+    device = "cuda"
+elif torch.backends.mps.is_available():
+    device = "mps"
+else:
+    device = "cpu"
+dtype = torch.float16 if device in {"cuda", "mps"} else torch.float32
+
+pipe = DiffusionPipeline.from_pretrained(model_id, torch_dtype=dtype)
+pipe.scheduler = PNDMScheduler.from_config(pipe.scheduler.config)
+pipe = pipe.to(device)
+
+generator_device = "cuda" if device == "cuda" else "cpu"
+generator = torch.Generator(device=generator_device).manual_seed(1337)
+result = pipe(
+    prompt="a tiny greenhouse glowing in a moonlit garden",
+    negative_prompt="",
+    num_inference_steps=50,
+    guidance_scale=7.5,
+    height=512,
+    width=512,
+    generator=generator,
+)
+result.images[0].save("clover-image-tiny.png")
+```
+
+The bundled `examples/generate.py` chooses CUDA, MPS, or CPU safely and writes
+the resolved settings next to the PNG:
+
+```bash
+python examples/generate.py \
+  --model "neonforestmist/Clover-Image-Tiny" \
+  --prompt "a tiny greenhouse glowing in a moonlit garden" \
+  --output clover-image-tiny.png
+```
+
+Seeded generation is repeatable only within the limits of the selected runtime.
+Different devices, dtypes, kernels, and dependency builds can produce different
+pixels. The bundled Mac example below was measured locally on an Apple M4 Pro
+with MPS and fp16: 18.21 seconds, exactly 51 U-Net calls, and 631,341,056 bytes
+of process-lifetime maximum RSS. It used the prompt “a compact modern library
+with arched windows” and seed 1469. The packaged safety checker ran and returned
+clear. This does not promise identical pixels or performance on another Mac.
+
+![Clover Image Tiny local MPS library example](assets/clover-image-tiny-local-mps-library-seed-1469.png)
+
+Its machine-readable evidence is bundled at
+`evidence/clover-image-tiny-local-mps-library-seed-1469.json`; the image
+SHA-256 is
+`f8830346f2a9c2b9a8c2a01d8f90e6925c93d667c1bcf998aa904a150589a742`.
+
+## Training lineage
+
+- Starting student:
+  `nota-ai/bk-sdm-tiny-2m@aad3e0e8ba61b7cb9f64869dc4e586f8ad9d3665`
+- Frozen teacher:
+  `CompVis/stable-diffusion-v1-4@133a221b8aa7292a167afc5127cb63fb5005638b`
+- Fine-tuning data: exactly 1,000 accepted image-caption pairs from
+  `Spawning/PD3M@2a5eb24a8dccf245acd8e56341761aee06da0bdf`
+- Split: 973 train, 17 validation, and 10 test records in one checksummed shard
+- Data gate: `CDLA-Permissive-2.0`; accepted items retain CC0-1.0 or Public
+  Domain Mark 1.0 provenance
+- Preprocessing: deterministic center crop and 512×512 JPEG conversion,
+  version `clover-pd3m-center-crop-512-jpeg95-v1`
+
+The 1,000 records describe only this Clover fine-tuning run. The starting
+student and teacher already contain knowledge learned from much larger upstream
+corpora. Their pinned model cards and weight licenses were verified, but the
+project does not have complete per-record provenance for all foundational
+pretraining behind those weights. In particular, the BK-SDM model card names
+LAION-Aesthetics V2 6.25+ and 2,256,472 pairs without the per-record evidence
+required by Clover's full release policy. This inherited gap is a material
+reason the package is labeled a research preview and not release-ready.
+
+See `DATA_PROVENANCE.md`, `MODEL_DATA_LICENSES.md`, the bundled CreativeML Open
+RAIL-M terms, and the package checksums for the portable evidence included here.
+
+## Intended use
+
+- Research and inspection of compact Stable Diffusion knowledge distillation
+- Reproducing the fixed conventional 50-step engineering examples
+- Comparing this early calibration checkpoint with its pinned starting student
+- Non-consequential creative experimentation subject to the model license
+
+## Limitations
+
+- The model was fine-tuned for only 500 optimizer steps on 1,000 pairs.
+- The eight-prompt gallery is an engineering-health subset, not a representative
+  quality, alignment, diversity, bias, or human-preference evaluation.
+- Results may omit requested objects, lose relationships or counts, produce
+  malformed anatomy and hands, render text poorly, or preserve/amplify biases
+  from upstream models and data.
+- The Stage B changes are modest and can make individual prompts worse.
+- The included pipeline is the conventional PyTorch/Diffusers path only.
+
+## Safety and out-of-scope use
+
+The upstream safety checker is included and was exercised in the recorded
+gallery run, but it is not a complete safety system and can miss harmful output
+or over-filter benign output. Applications should add appropriate prompt and
+output controls, human review, and policy enforcement.
+
+Do not use this preview for consequential decisions, identity claims, medical
+or legal conclusions, harassment, exploitation, illegal activity, or any use
+prohibited by CreativeML OpenRAIL-M. Review outputs before sharing them.
+
+## Licenses
+
+The model weights are a derivative under **CreativeML OpenRAIL-M**. The small
+example and packaging code is licensed separately under **Apache-2.0**. The
+PD3M dataset declaration and each accepted item's public-domain status remain
+separate from both licenses. Read the bundled license files and
+`MODEL_DATA_LICENSES.md`; this summary is not legal advice.

checksums.json

@@ -0,0 +1,31 @@
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+  "LICENSE": "be351ebe7ac01bcdbb018639aadcfd38f136b7dc3f2a3d4d3a24db51d1b210ef",
+  "LICENSE-CODE": "e26a0375b714267325c27905ba947fdc41ebc0b7a36940a49ae12379ed6208d6",
+  "LICENSE-MODEL-CREATIVEML-OPENRAIL-M.txt": "be351ebe7ac01bcdbb018639aadcfd38f136b7dc3f2a3d4d3a24db51d1b210ef",
+  "MODEL_DATA_LICENSES.md": "8f6b712826f9904561fb32038635612722be61cfd776da58fb61a4848a03148e",
+  "README.md": "b7e880416cb80103e2de5659256cad36e10ec6f05fd6a82e14d928d9905e7573",
+  "assets/clover-image-tiny-local-mps-library-seed-1469.png": "f8830346f2a9c2b9a8c2a01d8f90e6925c93d667c1bcf998aa904a150589a742",
+  "assets/clover-image-tiny-paired-contact-sheet.png": "8653d1105b7b0c56e2385a127336dbe9b3a1a03c8518edb4934353a9d8e13bfa",
+  "evidence/clover-image-tiny-local-mps-library-seed-1469.json": "1ddd86de0be992987214266720e0f341f25791402aae637065d6d09a6ea67b27",
+  "evidence/stage-b-inference-checksums.json": "d9a28d5fe6f5b675ee1b9db52e6d0493c8d3d357bb824eac590911acbd5c3ebc",
+  "examples/generate.py": "bba645e9a5ac0959da22e1ef61fd1ab24a2974221e77a95c6fdb4c4c03715840",
+  "feature_extractor/preprocessor_config.json": "205d45875859846dc1ca211b9a19f5db72f47e953b396954ee34d48d8e95c3c6",
+  "model_index.json": "792073e269e5caff40b3f8c553387540c17a5d900ed0e9cbfab309d650e708dd",
+  "requirements.txt": "9dbb74869a34e3b610f737bce8a9d2a20691fd0fa416cf6bb42354b78e0a3861",
+  "research_preview.json": "9d4e1ce0f592135a7bcd12a1ce9f1cd85558a650ce4f5661e38ffba58a4049bf",
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+  "safety_checker/model.safetensors": "57ecdfa243b170f9b4cb3eefaf0f64552ef78fc0bf0eb1c5b9675308447184f6",
+  "scheduler/scheduler_config.json": "184bc33ed887951dd86e37f20c878710c4e18e1c5fd4461256a3825679b53d15",
+  "stage_b_config.json": "4f915bdda1d3de4f383b41b8846b7a8d634bb37ff710f5127ac94ed0b5c76b94",
+  "text_encoder/config.json": "7fb4396af311adfc5247f22655b607c44223dbf4c143a07b2e8b2d024d7e31f0",
+  "text_encoder/model.safetensors": "660c6f5b1abae9dc498ac2d21e1347d2abdb0cf6c0c0c8576cd796491d9a6cdd",
+  "tokenizer/merges.txt": "9fd691f7c8039210e0fced15865466c65820d09b63988b0174bfe25de299051a",
+  "tokenizer/special_tokens_map.json": "c4864a9376a8401918425bed71fc14fc0e81f9b59ec45c1cf96cccb2df508eac",
+  "tokenizer/tokenizer_config.json": "c19f835a5e93d299b21dfee61c8f6a7cd06f5d83c8e828c013c25d2f36b47ccf",
+  "tokenizer/vocab.json": "4e6a66b6903c12d273a1a6645f761a2de07e239facfc52fd797b83a75014ca78",
+  "unet/config.json": "59f07bfeb2e53d480207436ce0ea2a30c0a3608d3bbf44c98458440167eff606",
+  "unet/diffusion_pytorch_model.safetensors": "f6e52380508473fcc355aae0288578205a06b324c7d873ee3b76b00e97beefc3",
+  "vae/config.json": "a51192fd731f5826ef0db722dc032b8c6f10456c5f626bc54da0e8514b899b40",
+  "vae/diffusion_pytorch_model.safetensors": "4fbcf0ebe55a0984f5a5e00d8c4521d52359af7229bb4d81890039d2aa16dd7c"
+}

evidence/clover-image-tiny-local-mps-library-seed-1469.json

@@ -0,0 +1 @@
+{"generation":{"denoiser_calls":51,"device":"mps","dtype":"float16","elapsed_seconds":18.208059416996548,"guidance_scale":7.5,"height":512,"negative_prompt":"","num_inference_steps":50,"prompt":"a compact modern library with arched windows","scheduler":"PNDMScheduler","seed":1469,"width":512},"image":{"filename":"library-seed-1469.png","format":"PNG","height":512,"mode":"RGB","pixel_mean":114.8316281636556,"pixel_standard_deviation":69.02280620757928,"sha256":"f8830346f2a9c2b9a8c2a01d8f90e6925c93d667c1bcf998aa904a150589a742","width":512},"kind":"clover-stage-b-local-generation-evidence","limitations":{"cross_hardware_pixel_identity":"not_claimed","iphone_or_coreml_result":false,"release_quality":"not_measured"},"memory":{"process_lifetime_max_rss_bytes":631341056,"rss_after_bytes":631341056,"rss_before_bytes":402030592,"sampled_process_peak_rss_bytes":624803840,"sampling_interval_seconds":0.05},"model":{"checkpoint_bundle_checksum":"384b6515f5f26838aea33ec9a941e06610a20764f0b8637c8b7b0667bfc0d447","checkpoint_checksum":"4a5b99ff18478742528a0d31c97dcee939b166a51be858721d40ad5984110893","config_hash":"80cf9395d1f587dc0c1d440d9f5b55c55c20703187998509bb306d19d463f597","dataset_manifest_checksum":"50c1249f1cb0d8d690a9acc451ca10c9432eb5a7f4e26f34acb5462096e72322","experiment_id":"clover-kd-20260712T050925Z-01KXABNHP0","optimizer_step":500,"package_checksums_sha256":"d9a28d5fe6f5b675ee1b9db52e6d0493c8d3d357bb824eac590911acbd5c3ebc"},"runtime":{"platform":"macOS-27.0-arm64-arm-64bit","python":"3.12.13","torch":"2.7.0"},"safety":{"host_review_note":"Automated filtering is imperfect; review generated output before sharing.","nsfw_content_detected":false,"packaged_checker_invoked":true},"schema_version":1}

evidence/stage-b-inference-checksums.json

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+{
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+  "safety_checker/config.json": "241bd8fb1ba6feff0d7421f7af0f85743711c5d76353626f71f7e2cc8009ac7c",
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+  "stage_b_config.json": "4f915bdda1d3de4f383b41b8846b7a8d634bb37ff710f5127ac94ed0b5c76b94",
+  "text_encoder/config.json": "7fb4396af311adfc5247f22655b607c44223dbf4c143a07b2e8b2d024d7e31f0",
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+  "tokenizer/special_tokens_map.json": "c4864a9376a8401918425bed71fc14fc0e81f9b59ec45c1cf96cccb2df508eac",
+  "tokenizer/tokenizer_config.json": "c19f835a5e93d299b21dfee61c8f6a7cd06f5d83c8e828c013c25d2f36b47ccf",
+  "tokenizer/vocab.json": "4e6a66b6903c12d273a1a6645f761a2de07e239facfc52fd797b83a75014ca78",
+  "unet/config.json": "59f07bfeb2e53d480207436ce0ea2a30c0a3608d3bbf44c98458440167eff606",
+  "unet/diffusion_pytorch_model.safetensors": "f6e52380508473fcc355aae0288578205a06b324c7d873ee3b76b00e97beefc3",
+  "vae/config.json": "a51192fd731f5826ef0db722dc032b8c6f10456c5f626bc54da0e8514b899b40",
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+}

examples/generate.py

@@ -0,0 +1,94 @@
+#!/usr/bin/env python3
+"""Generate one conventional 50-step Clover Image Tiny preview image."""
+
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+
+import torch
+from diffusers import DiffusionPipeline, PNDMScheduler
+
+
+def _runtime(requested: str) -> tuple[torch.device, torch.dtype]:
+    if requested == "auto":
+        if torch.cuda.is_available():
+            device = torch.device("cuda")
+        elif torch.backends.mps.is_available():
+            device = torch.device("mps")
+        else:
+            device = torch.device("cpu")
+    else:
+        device = torch.device(requested)
+    if device.type == "cuda" and not torch.cuda.is_available():
+        raise RuntimeError("CUDA was requested but is unavailable")
+    if device.type == "mps" and not torch.backends.mps.is_available():
+        raise RuntimeError("MPS was requested but is unavailable")
+    dtype = torch.float16 if device.type in {"cuda", "mps"} else torch.float32
+    return device, dtype
+
+
+def _parser() -> argparse.ArgumentParser:
+    parser = argparse.ArgumentParser(
+        description="Run Clover Image Tiny with its fixed conventional preview settings."
+    )
+    parser.add_argument("--model", required=True, help="Hub repository ID or local directory")
+    parser.add_argument("--prompt", required=True)
+    parser.add_argument("--seed", type=int, default=1337)
+    parser.add_argument("--output", type=Path, default=Path("clover-image-tiny.png"))
+    parser.add_argument("--device", choices=("auto", "cuda", "mps", "cpu"), default="auto")
+    parser.add_argument("--local-files-only", action="store_true")
+    return parser
+
+
+def main() -> int:
+    args = _parser().parse_args()
+    device, dtype = _runtime(args.device)
+    pipe = DiffusionPipeline.from_pretrained(
+        args.model,
+        torch_dtype=dtype,
+        local_files_only=args.local_files_only,
+    )
+    pipe.scheduler = PNDMScheduler.from_config(pipe.scheduler.config)
+    pipe = pipe.to(device)
+    generator_device = "cuda" if device.type == "cuda" else "cpu"
+    generator = torch.Generator(device=generator_device).manual_seed(args.seed)
+    with torch.inference_mode():
+        result = pipe(
+            prompt=args.prompt,
+            negative_prompt="",
+            num_inference_steps=50,
+            guidance_scale=7.5,
+            height=512,
+            width=512,
+            generator=generator,
+        )
+    if not result.images:
+        raise RuntimeError("the pipeline returned no images")
+    args.output.parent.mkdir(parents=True, exist_ok=True)
+    result.images[0].save(args.output)
+    metadata = {
+        "model": args.model,
+        "prompt": args.prompt,
+        "negative_prompt": "",
+        "seed": args.seed,
+        "scheduler": type(pipe.scheduler).__name__,
+        "num_inference_steps": 50,
+        "guidance_scale": 7.5,
+        "height": 512,
+        "width": 512,
+        "device": device.type,
+        "dtype": str(dtype).removeprefix("torch."),
+        "nsfw_content_detected": getattr(result, "nsfw_content_detected", None),
+        "cross_device_pixel_identity_claimed": False,
+        "usage_label": "RESEARCH PREVIEW - PRODUCTION PILOT - NOT RELEASE-READY",
+    }
+    metadata_path = args.output.with_suffix(args.output.suffix + ".json")
+    metadata_path.write_text(json.dumps(metadata, indent=2) + "\n", encoding="utf-8")
+    print(json.dumps({"output": str(args.output), "metadata": str(metadata_path), **metadata}))
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

feature_extractor/preprocessor_config.json

@@ -0,0 +1,27 @@
+{
+  "crop_size": {
+    "height": 224,
+    "width": 224
+  },
+  "do_center_crop": true,
+  "do_convert_rgb": true,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.48145466,
+    0.4578275,
+    0.40821073
+  ],
+  "image_processor_type": "CLIPImageProcessor",
+  "image_std": [
+    0.26862954,
+    0.26130258,
+    0.27577711
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}

model_index.json

@@ -0,0 +1,37 @@
+{
+  "_class_name": "StableDiffusionPipeline",
+  "_diffusers_version": "0.39.0",
+  "feature_extractor": [
+    "transformers",
+    "CLIPImageProcessor"
+  ],
+  "image_encoder": [
+    null,
+    null
+  ],
+  "requires_safety_checker": true,
+  "safety_checker": [
+    "stable_diffusion",
+    "StableDiffusionSafetyChecker"
+  ],
+  "scheduler": [
+    "diffusers",
+    "PNDMScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "unet": [
+    "diffusers",
+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

requirements.txt

@@ -0,0 +1,11 @@
+accelerate==1.14.0
+diffusers==0.39.0
+ftfy==6.3.1
+huggingface-hub==0.36.2
+numpy==2.2.6
+pillow==12.3.0
+safetensors==0.8.0
+tokenizers==0.22.2
+torch==2.7.0
+torchvision==0.22.0
+transformers==4.57.6

research_preview.json

@@ -0,0 +1,168 @@
+{
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+    "experiment_id": "clover-kd-20260712T050925Z-01KXABNHP0",
+    "optimizer_step": 500
+  },
+  "data": {
+    "dataset_id": "Spawning/PD3M",
+    "dataset_license_id": "CDLA-Permissive-2.0",
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+    "contact_sheet_sha256": "8653d1105b7b0c56e2385a127336dbe9b3a1a03c8518edb4934353a9d8e13bfa",
+    "evaluation_scope": "eight-prompt-engineering-health-subset",
+    "human_review": "not_measured",
+    "image_pair_count": 8,
+    "kind": "stage-b-paired-engineering-gallery",
+    "quality_decisional": false,
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+    "source_report_sha256": "d09ca159c4face6d4ab895f67afe5c52fa03adf2647d01121527be4f501f4c71",
+    "status": "validated"
+  },
+  "hf_repo_id": "neonforestmist/Clover-Image-Tiny",
+  "kind": "clover-stage-b-hf-research-preview",
+  "licenses": {
+    "code": {
+      "id": "Apache-2.0",
+      "path": "LICENSE-CODE",
+      "sha256": "e26a0375b714267325c27905ba947fdc41ebc0b7a36940a49ae12379ed6208d6"
+    },
+    "model_weights": {
+      "id": "CreativeML OpenRAIL-M",
+      "path": "LICENSE-MODEL-CREATIVEML-OPENRAIL-M.txt",
+      "sha256": "be351ebe7ac01bcdbb018639aadcfd38f136b7dc3f2a3d4d3a24db51d1b210ef"
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+    "human_review": "not_measured",
+    "quality_evaluation": "not_measured"
+  },
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+    "negative_prompt": "",
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+    "pipeline": "StableDiffusionPipeline",
+    "scheduler": "PNDMScheduler",
+    "width": 512
+  },
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+  "source_package": {
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+    "checksums_sha256": "d9a28d5fe6f5b675ee1b9db52e6d0493c8d3d357bb824eac590911acbd5c3ebc",
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+      "weight_dtype": "float16"
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+  "training_stage": "stage_b_knowledge_distillation",
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+}

safety_checker/config.json

@@ -0,0 +1,46 @@
+{
+  "architectures": [
+    "StableDiffusionSafetyChecker"
+  ],
+  "dtype": "float16",
+  "initializer_factor": 1.0,
+  "logit_scale_init_value": 2.6592,
+  "model_type": "clip",
+  "projection_dim": 768,
+  "text_config": {
+    "attention_dropout": 0.0,
+    "dropout": 0.0,
+    "dtype": "float16",
+    "hidden_act": "quick_gelu",
+    "hidden_size": 768,
+    "initializer_factor": 1.0,
+    "initializer_range": 0.02,
+    "intermediate_size": 3072,
+    "layer_norm_eps": 1e-05,
+    "max_position_embeddings": 77,
+    "model_type": "clip_text_model",
+    "num_attention_heads": 12,
+    "num_hidden_layers": 12,
+    "projection_dim": 512,
+    "vocab_size": 49408
+  },
+  "transformers_version": "4.57.6",
+  "vision_config": {
+    "attention_dropout": 0.0,
+    "dropout": 0.0,
+    "dtype": "float16",
+    "hidden_act": "quick_gelu",
+    "hidden_size": 1024,
+    "image_size": 224,
+    "initializer_factor": 1.0,
+    "initializer_range": 0.02,
+    "intermediate_size": 4096,
+    "layer_norm_eps": 1e-05,
+    "model_type": "clip_vision_model",
+    "num_attention_heads": 16,
+    "num_channels": 3,
+    "num_hidden_layers": 24,
+    "patch_size": 14,
+    "projection_dim": 512
+  }
+}

safety_checker/model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:57ecdfa243b170f9b4cb3eefaf0f64552ef78fc0bf0eb1c5b9675308447184f6
+size 608016280

scheduler/scheduler_config.json

@@ -0,0 +1,15 @@
+{
+  "_class_name": "PNDMScheduler",
+  "_diffusers_version": "0.39.0",
+  "beta_end": 0.012,
+  "beta_schedule": "scaled_linear",
+  "beta_start": 0.00085,
+  "clip_sample": false,
+  "num_train_timesteps": 1000,
+  "prediction_type": "epsilon",
+  "set_alpha_to_one": false,
+  "skip_prk_steps": true,
+  "steps_offset": 1,
+  "timestep_spacing": "leading",
+  "trained_betas": null
+}

stage_b_config.json

@@ -0,0 +1,74 @@
+{
+  "_class_name": "StableDiffusionPipeline",
+  "base_components": {
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