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Add full GGUF quant ladder for Gemma-4-12b-it-Abliterated

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README.md CHANGED
@@ -1,70 +1,29 @@
1
  ---
2
  base_model: Carlosian/Gemma-4-12b-it-Abliterated
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  base_model_relation: quantized
4
- license: gemma
5
- license_link: https://ai.google.dev/gemma/terms
6
- language:
7
- - en
8
  pipeline_tag: text-generation
9
  tags:
10
- - gemma
11
- - gemma4
12
  - abliterated
13
  - uncensored
14
- - gguf
15
  - llama.cpp
16
- - imatrix
17
- - quantized
18
- - research
19
  ---
20
 
21
- # Gemma-4-12B-ITAbliterated · GGUF
22
-
23
- **imatrix-quantized GGUF builds** of [`Carlosian/Gemma-4-12b-it-Abliterated`](https://huggingface.co/Carlosian/Gemma-4-12b-it-Abliterated) — the Stage-1 **abliterated** (refusal-removed) Gemma-4-12B base, with **self-harm / suicide guardrails deliberately retained**. For the method, validation (97.5% refusal removal, no cognitive damage), and responsible-use terms, see the parent repo.
24
-
25
- These are **text-only** GGUFs: the source is a unified multimodal checkpoint, and only the language tower (`gemma4` arch, 48 layers) is converted — standard for llama.cpp text inference.
26
-
27
- > ⚠️ Dual-use research model. Its general instruction-refusal behavior has been removed. Use is governed by the [Gemma Terms of Use](https://ai.google.dev/gemma/terms) and [Prohibited Use Policy](https://ai.google.dev/gemma/prohibited_use_policy).
28
-
29
- ## Quant ladder
30
-
31
- All quants below `Q6_K` are built with an **importance matrix** (imatrix) computed on the Q8_0 over the `calibration_datav3` corpus (100 chunks × 512 ctx), which measurably improves the low-bit quants.
32
-
33
- | File | Quant | Size | Notes |
34
- |---|---|---:|---|
35
- | `gemma4-12b-abliterated-IQ4_XS.gguf` | IQ4_XS | 6.6 GB | smallest; imatrix-dependent, good quality/size |
36
- | `gemma4-12b-abliterated-Q4_K_M.gguf` | Q4_K_M | 7.4 GB | **recommended** balance |
37
- | `gemma4-12b-abliterated-Q5_K_M.gguf` | Q5_K_M | 8.5 GB | higher quality |
38
- | `gemma4-12b-abliterated-Q6_K.gguf` | Q6_K | 9.8 GB | near-lossless |
39
- | `gemma4-12b-abliterated-Q8_0.gguf` | Q8_0 | 12.7 GB | effectively lossless |
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- | `gemma4-12b-abliterated.imatrix` | — | 7.5 MB | importance matrix (for re-quantizing) |
41
-
42
- Tested on a Radeon 890M (Vulkan, `-ngl 99`); the Q4_K_M of these weights ran the residual-refusal audit at ~10 tok/s with 0.0% hard-refusal.
43
-
44
- ## Usage
45
-
46
- **llama.cpp**
47
- ```bash
48
- llama-cli -m gemma4-12b-abliterated-Q4_K_M.gguf -ngl 99 -c 8192 \
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- -p "Explain how a buffer overflow works."
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- # or serve an OpenAI-compatible endpoint:
51
- llama-server -m gemma4-12b-abliterated-Q4_K_M.gguf -ngl 99 -c 8192
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- ```
53
-
54
- **Ollama**
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- ```bash
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- # Modelfile: FROM ./gemma4-12b-abliterated-Q4_K_M.gguf
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- ollama create gemma4-abliterated -f Modelfile && ollama run gemma4-abliterated
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- ```
59
-
60
- Always use the Gemma chat template (the GGUF embeds it). Requires a llama.cpp build with `gemma4` support.
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-
62
- ## Provenance
63
 
64
- - Source weights: [`Carlosian/Gemma-4-12b-it-Abliterated`](https://huggingface.co/Carlosian/Gemma-4-12b-it-Abliterated) (bf16)
65
- - Converted + quantized with llama.cpp; imatrix via `calibration_datav3`
66
- - Selective abliteration with self-harm/suicide guardrails retained — see parent repo and the Nous-Heretic method paper.
67
 
68
- ## License
 
 
 
 
 
 
 
 
69
 
70
- Derivative of Gemma distributed under the [Gemma Terms of Use](https://ai.google.dev/gemma/terms) and [Prohibited Use Policy](https://ai.google.dev/gemma/prohibited_use_policy).
 
1
  ---
2
  base_model: Carlosian/Gemma-4-12b-it-Abliterated
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  base_model_relation: quantized
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+ library_name: gguf
 
 
 
5
  pipeline_tag: text-generation
6
  tags:
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+ - gguf
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+ - quantized
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  - abliterated
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  - uncensored
 
11
  - llama.cpp
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+ license: other
 
 
13
  ---
14
 
15
+ # Gemma-4-12b-it-AbliteratedGGUF quant ladder
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
16
 
17
+ Quantized GGUF builds of [`Carlosian/Gemma-4-12b-it-Abliterated`](https://huggingface.co/Carlosian/Gemma-4-12b-it-Abliterated) for llama.cpp / Ollama / LM Studio.
 
 
18
 
19
+ | Quant | Typical use |
20
+ |-------|-------------|
21
+ | Q2_K | smallest / extreme low VRAM |
22
+ | Q3_K_S / Q3_K_M | low VRAM |
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+ | Q4_0 / Q4_K_S / Q4_K_M | **recommended default (Q4_K_M)** |
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+ | Q5_K_S / Q5_K_M | higher quality |
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+ | Q6_K | near-lossless |
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+ | Q8_0 | highest quality quant |
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+ | F16 | full intermediate (large) |
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29
+ Built with llama.cpp on Thunder Compute (A100). Generated 2026-07-20.
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+ INFO:hf-to-gguf:Loading model: Gemma-4-12b-it-Abliterated
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+ WARNING:hf-to-gguf:Failed to load model config from /home/ubuntu/ladder/models/Gemma-4-12b-it-Abliterated: The checkpoint you are trying to load has model type `gemma4_unified` but Transformers does not recognize this architecture. This could be because of an issue with the checkpoint, or because your version of Transformers is out of date.
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+
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+ You can update Transformers with the command `pip install --upgrade transformers`. If this does not work, and the checkpoint is very new, then there may not be a release version that supports this model yet. In this case, you can get the most up-to-date code by installing Transformers from source with the command `pip install git+https://github.com/huggingface/transformers.git`
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+ WARNING:hf-to-gguf:Trying to load config.json instead
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+ INFO:hf-to-gguf:Model architecture: Gemma4UnifiedForConditionalGeneration
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+ WARNING:hf-to-gguf:Failed to load model config from /home/ubuntu/ladder/models/Gemma-4-12b-it-Abliterated: The checkpoint you are trying to load has model type `gemma4_unified` but Transformers does not recognize this architecture. This could be because of an issue with the checkpoint, or because your version of Transformers is out of date.
8
+
9
+ You can update Transformers with the command `pip install --upgrade transformers`. If this does not work, and the checkpoint is very new, then there may not be a release version that supports this model yet. In this case, you can get the most up-to-date code by installing Transformers from source with the command `pip install git+https://github.com/huggingface/transformers.git`
10
+ WARNING:hf-to-gguf:Trying to load config.json instead
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+ INFO:hf-to-gguf:gguf: indexing model part 'model.safetensors'
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+ INFO:gguf.gguf_writer:gguf: This GGUF file is for Little Endian only
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171
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176
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177
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178
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179
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180
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181
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184
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185
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186
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198
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199
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200
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201
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202
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203
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204
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205
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206
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207
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208
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209
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210
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211
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212
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213
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214
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215
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216
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217
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218
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219
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220
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221
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222
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223
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224
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225
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226
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227
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228
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229
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230
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231
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232
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233
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234
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235
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236
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237
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238
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239
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240
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241
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242
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243
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244
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245
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246
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247
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248
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249
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250
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251
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252
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253
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254
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255
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256
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257
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258
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259
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260
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261
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262
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263
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264
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454
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636
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637
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639
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640
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641
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643
+ INFO:hf-to-gguf:blk.7.post_attention_norm.weight, torch.bfloat16 --> F32, shape = {3840}
644
+ INFO:hf-to-gguf:blk.7.post_ffw_norm.weight, torch.bfloat16 --> F32, shape = {3840}
645
+ INFO:hf-to-gguf:blk.7.ffn_norm.weight, torch.bfloat16 --> F32, shape = {3840}
646
+ INFO:hf-to-gguf:blk.7.attn_k_norm.weight, torch.bfloat16 --> F32, shape = {256}
647
+ INFO:hf-to-gguf:blk.7.attn_k.weight, torch.bfloat16 --> F16, shape = {3840, 2048}
648
+ INFO:hf-to-gguf:blk.7.attn_output.weight, torch.bfloat16 --> F16, shape = {4096, 3840}
649
+ INFO:hf-to-gguf:blk.7.attn_q_norm.weight, torch.bfloat16 --> F32, shape = {256}
650
+ INFO:hf-to-gguf:blk.7.attn_q.weight, torch.bfloat16 --> F16, shape = {3840, 4096}
651
+ INFO:hf-to-gguf:blk.7.attn_v.weight, torch.bfloat16 --> F16, shape = {3840, 2048}
652
+ INFO:hf-to-gguf:blk.8.attn_norm.weight, torch.bfloat16 --> F32, shape = {3840}
653
+ INFO:hf-to-gguf:blk.8.layer_output_scale.weight, torch.bfloat16 --> F32, shape = {1}
654
+ INFO:hf-to-gguf:blk.8.ffn_down.weight, torch.bfloat16 --> F16, shape = {15360, 3840}
655
+ INFO:hf-to-gguf:blk.8.ffn_gate.weight, torch.bfloat16 --> F16, shape = {3840, 15360}
656
+ INFO:hf-to-gguf:blk.8.ffn_up.weight, torch.bfloat16 --> F16, shape = {3840, 15360}
657
+ INFO:hf-to-gguf:blk.8.post_attention_norm.weight, torch.bfloat16 --> F32, shape = {3840}
658
+ INFO:hf-to-gguf:blk.8.post_ffw_norm.weight, torch.bfloat16 --> F32, shape = {3840}
659
+ INFO:hf-to-gguf:blk.8.ffn_norm.weight, torch.bfloat16 --> F32, shape = {3840}
660
+ INFO:hf-to-gguf:blk.8.attn_k_norm.weight, torch.bfloat16 --> F32, shape = {256}
661
+ INFO:hf-to-gguf:blk.8.attn_k.weight, torch.bfloat16 --> F16, shape = {3840, 2048}
662
+ INFO:hf-to-gguf:blk.8.attn_output.weight, torch.bfloat16 --> F16, shape = {4096, 3840}
663
+ INFO:hf-to-gguf:blk.8.attn_q_norm.weight, torch.bfloat16 --> F32, shape = {256}
664
+ INFO:hf-to-gguf:blk.8.attn_q.weight, torch.bfloat16 --> F16, shape = {3840, 4096}
665
+ INFO:hf-to-gguf:blk.8.attn_v.weight, torch.bfloat16 --> F16, shape = {3840, 2048}
666
+ INFO:hf-to-gguf:blk.9.attn_norm.weight, torch.bfloat16 --> F32, shape = {3840}
667
+ INFO:hf-to-gguf:blk.9.layer_output_scale.weight, torch.bfloat16 --> F32, shape = {1}
668
+ INFO:hf-to-gguf:blk.9.ffn_down.weight, torch.bfloat16 --> F16, shape = {15360, 3840}
669
+ INFO:hf-to-gguf:blk.9.ffn_gate.weight, torch.bfloat16 --> F16, shape = {3840, 15360}
670
+ INFO:hf-to-gguf:blk.9.ffn_up.weight, torch.bfloat16 --> F16, shape = {3840, 15360}
671
+ INFO:hf-to-gguf:blk.9.post_attention_norm.weight, torch.bfloat16 --> F32, shape = {3840}
672
+ INFO:hf-to-gguf:blk.9.post_ffw_norm.weight, torch.bfloat16 --> F32, shape = {3840}
673
+ INFO:hf-to-gguf:blk.9.ffn_norm.weight, torch.bfloat16 --> F32, shape = {3840}
674
+ INFO:hf-to-gguf:blk.9.attn_k_norm.weight, torch.bfloat16 --> F32, shape = {256}
675
+ INFO:hf-to-gguf:blk.9.attn_k.weight, torch.bfloat16 --> F16, shape = {3840, 2048}
676
+ INFO:hf-to-gguf:blk.9.attn_output.weight, torch.bfloat16 --> F16, shape = {4096, 3840}
677
+ INFO:hf-to-gguf:blk.9.attn_q_norm.weight, torch.bfloat16 --> F32, shape = {256}
678
+ INFO:hf-to-gguf:blk.9.attn_q.weight, torch.bfloat16 --> F16, shape = {3840, 4096}
679
+ INFO:hf-to-gguf:blk.9.attn_v.weight, torch.bfloat16 --> F16, shape = {3840, 2048}
680
+ INFO:hf-to-gguf:output_norm.weight, torch.bfloat16 --> F32, shape = {3840}
681
+ INFO:hf-to-gguf:Set meta model
682
+ INFO:hf-to-gguf:Set model parameters
683
+ INFO:hf-to-gguf:gguf: context length = 262144
684
+ INFO:hf-to-gguf:gguf: embedding length = 3840
685
+ INFO:hf-to-gguf:gguf: feed forward length = 15360
686
+ INFO:hf-to-gguf:gguf: head count = 16
687
+ INFO:hf-to-gguf:gguf: key-value head count = 8
688
+ WARNING:hf-to-gguf:Unknown RoPE type: proportional
689
+ INFO:hf-to-gguf:gguf: rope scaling type = NONE
690
+ INFO:hf-to-gguf:gguf: rope theta = 1000000.0
691
+ INFO:hf-to-gguf:gguf: rope theta swa = 10000.0
692
+ INFO:hf-to-gguf:gguf: rms norm epsilon = 1e-06
693
+ INFO:hf-to-gguf:gguf: file type = 1
694
+ WARNING:gguf.gguf_writer:Duplicated key name 'gemma4.context_length', overwriting it with new value 262144 of type UINT32
695
+ WARNING:gguf.gguf_writer:Duplicated key name 'gemma4.attention.head_count', overwriting it with new value 16 of type UINT32
696
+ WARNING:gguf.gguf_writer:Duplicated key name 'gemma4.attention.layer_norm_rms_epsilon', overwriting it with new value 1e-06 of type FLOAT32
697
+ WARNING:gguf.gguf_writer:Duplicated key name 'gemma4.attention.key_length', overwriting it with new value 256 of type UINT32
698
+ WARNING:gguf.gguf_writer:Duplicated key name 'gemma4.attention.value_length', overwriting it with new value 256 of type UINT32
699
+ WARNING:gguf.gguf_writer:Duplicated key name 'gemma4.rope.freq_base', overwriting it with new value 1000000.0 of type FLOAT32
700
+ WARNING:gguf.gguf_writer:Duplicated key name 'gemma4.attention.head_count_kv', overwriting it with new value 8 of type UINT32
701
+ WARNING:gguf.gguf_writer:Duplicated key name 'gemma4.attention.key_length', overwriting it with new value 512 of type UINT32
702
+ WARNING:gguf.gguf_writer:Duplicated key name 'gemma4.attention.value_length', overwriting it with new value 512 of type UINT32
703
+ WARNING:gguf.gguf_writer:Duplicated key name 'gemma4.attention.head_count_kv', overwriting it with new value [8, 8, 8, 8, 8, 1, 8, 8, 8, 8, 8, 1, 8, 8, 8, 8, 8, 1, 8, 8, 8, 8, 8, 1, 8, 8, 8, 8, 8, 1, 8, 8, 8, 8, 8, 1, 8, 8, 8, 8, 8, 1, 8, 8, 8, 8, 8, 1] of type ARRAY
704
+ INFO:hf-to-gguf:Set model quantization version
705
+ INFO:hf-to-gguf:Set model tokenizer
706
+ /usr/local/lib/python3.12/dist-packages/sklearn/utils/_param_validation.py:14: UserWarning: A NumPy version >=2.0.0 and <2.8.0 is required for this version of SciPy (detected version 1.26.4)
707
+ from scipy.sparse import csr_array, issparse
708
+ /usr/local/lib/python3.12/dist-packages/scipy/sparse/_sputils.py:17: FutureWarning: In the future `np.long` will be defined as the corresponding NumPy scalar.
709
+ np.uintc, np.long, np.ulong, np.longlong, np.ulonglong,
710
+ /usr/local/lib/python3.12/dist-packages/scipy/sparse/_sputils.py:17: FutureWarning: In the future `np.long` will be defined as the corresponding NumPy scalar.
711
+ np.uintc, np.long, np.ulong, np.longlong, np.ulonglong,
712
+ Traceback (most recent call last):
713
+ File "/home/ubuntu/ladder/llama.cpp/gguf-py/gguf/vocab.py", line 574, in __init__
714
+ from transformers import AutoTokenizer
715
+ File "/home/ubuntu/.local/lib/python3.12/site-packages/transformers/utils/import_utils.py", line 2317, in __getattr__
716
+ module = self._get_module(self._class_to_module[name])
717
+ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
718
+ File "/home/ubuntu/.local/lib/python3.12/site-packages/transformers/utils/import_utils.py", line 2347, in _get_module
719
+ raise e
720
+ File "/home/ubuntu/.local/lib/python3.12/site-packages/transformers/utils/import_utils.py", line 2345, in _get_module
721
+ return importlib.import_module("." + module_name, self.__name__)
722
+ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
723
+ File "/usr/lib/python3.12/importlib/__init__.py", line 90, in import_module
724
+ return _bootstrap._gcd_import(name[level:], package, level)
725
+ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
726
+ File "/home/ubuntu/.local/lib/python3.12/site-packages/transformers/models/auto/tokenization_auto.py", line 40, in <module>
727
+ from .auto_factory import _LazyAutoMapping
728
+ File "/home/ubuntu/.local/lib/python3.12/site-packages/transformers/models/auto/auto_factory.py", line 43, in <module>
729
+ from ...generation import GenerationMixin
730
+ ImportError: cannot import name 'GenerationMixin' from 'transformers.generation' (/home/ubuntu/.local/lib/python3.12/site-packages/transformers/generation/__init__.py). Did you mean: 'GenerationMode'?
731
+
732
+ The above exception was the direct cause of the following exception:
733
+
734
+ Traceback (most recent call last):
735
+ File "/home/ubuntu/ladder/llama.cpp/convert_hf_to_gguf.py", line 296, in <module>
736
+ main()
737
+ File "/home/ubuntu/ladder/llama.cpp/convert_hf_to_gguf.py", line 290, in main
738
+ model_instance.write()
739
+ File "/home/ubuntu/ladder/llama.cpp/conversion/base.py", line 1026, in write
740
+ self.prepare_metadata(vocab_only=False)
741
+ File "/home/ubuntu/ladder/llama.cpp/conversion/base.py", line 1193, in prepare_metadata
742
+ self.set_vocab()
743
+ File "/home/ubuntu/ladder/llama.cpp/conversion/gemma.py", line 626, in set_vocab
744
+ vocab = gguf.LlamaHfVocab(self.dir_model)
745
+ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
746
+ File "/home/ubuntu/ladder/llama.cpp/gguf-py/gguf/vocab.py", line 576, in __init__
747
+ raise ImportError(
748
+ ImportError: To use LlamaHfVocab, please install the `transformers` package. You can install it with `pip install transformers`.
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