Publish validated Clover Image Tiny research preview

README.md

@@ -37,10 +37,10 @@ claim of uniformly better output than its starting model.
 | Checkpoint-bundle SHA-256 | `384b6515f5f26838aea33ec9a941e06610a20764f0b8637c8b7b0667bfc0d447` |
 | Resolved-config SHA-256 | `80cf9395d1f587dc0c1d440d9f5b55c55c20703187998509bb306d19d463f597` |
 | Dataset-manifest SHA-256 | `50c1249f1cb0d8d690a9acc451ca10c9432eb5a7f4e26f34acb5462096e72322` |
-| Package bytes | `1671489892` |
+| Package bytes | `1671492371` |
 | Package files | `30` |
 | Validated Stage B source-package checksums SHA-256 | `d9a28d5fe6f5b675ee1b9db52e6d0493c8d3d357bb824eac590911acbd5c3ebc` |
-| Builder source commit | `1880c3eb55133e8b7b1786ddea8e732d16a2f902` |
+| Builder source commit | `e6079eec2b91c5d026bfb461fd6c844a98b888ec` |
 
 The checkpoint completed 500 optimizer steps, 4,000 microsteps, and 4,000
 sample presentations. All 500 recorded training rows were finite and had a
@@ -64,15 +64,91 @@ 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
+## Run locally
 
-Install the pinned preview environment:
+This is a conventional PyTorch/Diffusers model, so it can run on macOS,
+Windows, or Linux. Use Python 3.11 or 3.12 and allow about 2 GB of free disk
+space for the model itself. Mac MPS is the only local runtime measured for this
+preview; Windows/Linux CUDA and CPU execution are supported by the runner but
+their performance is not claimed here.
+
+### macOS Apple silicon — MPS
+
+These commands download a complete local copy, install the pinned runtime in
+an isolated environment, and generate through MPS:
 
 ```bash
-python -m pip install -r requirements.txt
+mkdir clover-image-tiny-local
+cd clover-image-tiny-local
+
+python3.12 -m venv .venv
+source .venv/bin/activate
+python -m pip install --upgrade pip
+python -m pip install "huggingface-hub==0.36.2"
+
+hf download "neonforestmist/Clover-Image-Tiny" --local-dir model
+python -m pip install -r model/requirements.txt
+
+python model/examples/generate.py \
+  --model model \
+  --device mps \
+  --local-files-only \
+  --prompt "a compact modern library with arched windows" \
+  --seed 1469 \
+  --output clover-image-tiny.png
+
+open clover-image-tiny.png
+```
+
+If `python3.12` is not installed but Python 3.11 is, use `python3.11` instead.
+After the first download, `--local-files-only` keeps inference offline. The
+script writes the resolved runtime settings beside the PNG as
+`clover-image-tiny.png.json`. This is the PyTorch/Diffusers model; no Core ML or
+iPhone package is required or included.
+
+### Windows — PowerShell
+
+On Windows, the same runner automatically selects an available NVIDIA CUDA GPU
+and otherwise falls back to CPU:
+
+```powershell
+mkdir clover-image-tiny-local
+cd clover-image-tiny-local
+
+py -3.12 -m venv .venv
+.venv\Scripts\Activate.ps1
+python -m pip install --upgrade pip
+python -m pip install "huggingface-hub==0.36.2"
+
+hf download "neonforestmist/Clover-Image-Tiny" --local-dir model
+python -m pip install -r model\requirements.txt
+
+python model\examples\generate.py `
+  --model model `
+  --device auto `
+  --local-files-only `
+  --prompt "a compact modern library with arched windows" `
+  --seed 1469 `
+  --output clover-image-tiny.png
+
+Invoke-Item .\clover-image-tiny.png
 ```
 
-Then generate with the conventional configuration used for the gallery:
+Use `py -3.11` if that is the installed supported Python. Check
+`python -c "import torch; print(torch.cuda.is_available())"` after installation;
+`False` means `--device auto` will use CPU. A Windows AMD/DirectML path is not
+included or validated.
+
+### Linux
+
+Use the macOS shell flow with `python3.11` or `python3.12`, and replace
+`--device mps` with `--device auto`. It selects CUDA when PyTorch can see an
+NVIDIA GPU and otherwise uses CPU.
+
+### Python API
+
+The equivalent conventional configuration, with automatic CUDA/MPS/CPU
+selection, is:
 
 ```python
 import torch

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@@ -13,7 +13,7 @@
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research_preview.json

@@ -1,6 +1,6 @@
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@@ -27,7 +27,7 @@
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@@ -116,7 +116,7 @@
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     "quality_evaluation": "not_measured"
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