Image-Text-to-Text
Transformers
Safetensors
gemma4
quantized
w8a16
fp8
conversational
compressed-tensors
Instructions to use hoborific/Gemma-4-Giftige-Blume-31B-v1-W8A16-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hoborific/Gemma-4-Giftige-Blume-31B-v1-W8A16-FP8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="hoborific/Gemma-4-Giftige-Blume-31B-v1-W8A16-FP8") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("hoborific/Gemma-4-Giftige-Blume-31B-v1-W8A16-FP8") model = AutoModelForMultimodalLM.from_pretrained("hoborific/Gemma-4-Giftige-Blume-31B-v1-W8A16-FP8", device_map="auto") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use hoborific/Gemma-4-Giftige-Blume-31B-v1-W8A16-FP8 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "hoborific/Gemma-4-Giftige-Blume-31B-v1-W8A16-FP8" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hoborific/Gemma-4-Giftige-Blume-31B-v1-W8A16-FP8", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/hoborific/Gemma-4-Giftige-Blume-31B-v1-W8A16-FP8
- SGLang
How to use hoborific/Gemma-4-Giftige-Blume-31B-v1-W8A16-FP8 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "hoborific/Gemma-4-Giftige-Blume-31B-v1-W8A16-FP8" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hoborific/Gemma-4-Giftige-Blume-31B-v1-W8A16-FP8", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "hoborific/Gemma-4-Giftige-Blume-31B-v1-W8A16-FP8" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hoborific/Gemma-4-Giftige-Blume-31B-v1-W8A16-FP8", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use hoborific/Gemma-4-Giftige-Blume-31B-v1-W8A16-FP8 with Docker Model Runner:
docker model run hf.co/hoborific/Gemma-4-Giftige-Blume-31B-v1-W8A16-FP8
Upload README.md with huggingface_hub
Browse files
README.md
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- google/gemma-4-31B-it
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- MRockatansky/Gemma-4-31B-storymaxxed
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- MRockatansky/Gemma-4-31B-storymaxxed2
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- LatitudeGames/Equinox-31B
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- sophosympatheia/Mero-Artemis-31B-v0.3.1
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- AuriAetherwiing/G4-31B-Musica-v1
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- llmfan46/gemma-4-Ortenzya-The-Creative-Wordsmith-31B-it-uncensored-heretic
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- Jackrong/Gemopus-4-31B-it
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tags:
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- non-reasoning
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.blume-wrapper {
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background-image: radial-gradient(circle at 10% 10%, rgba(168, 85, 247, 0.08) 0%, transparent 40%), radial-gradient(circle at 90% 90%, rgba(34, 197, 94, 0.06) 0%, transparent 40%);
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background: linear-gradient(90deg, #c522af, #c6f755, #c522af);
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filter: drop-shadow(0 0 15px rgba(34, 197, 94, 0.4));
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border-radius: 8px 20px 20px 8px;
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box-shadow: inset 0 -2px 10px rgba(34, 197, 94, 0.05), 0 10px 30px rgba(0,0,0,0.5);
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<div style="font-size: 0.9rem; color: #94a3b8; margin-bottom: 15px; text-align: center;">by Nimbz</div>
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<img src="giftige-blume-31b-title.png" width="100%" style="border-radius: 15px; border: 1px solid #14532d; box-shadow: 0 15px 40px rgba(0,0,0,0.6); margin-bottom: 15px;">
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<h1 class="toxic-title"> 🌺 Giftige-Blume-31B-v1 🌻 </h1>
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<div class="subtitle">Beautiful in Prose • Rich in Variance</div>
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<div style="margin-bottom: 15px;">While Giftige-Blume-31B-v2 aims to be more logical and prompt adherent, Giftige-Blume-31B-v1 brings in a lot of mixed roleplay-centered models as it's knowledge core to provide rich and diverse roleplay scenarios, carrying over the genuine character portrayal, diverse prose and writing styles with each swipe.</div>
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<div>This model is made for a wide range of roleplay scenarios, with the goal to impersonate characters as they are described and not how the user wants them to be mid-chat. Expect uncensored roleplay without the deep-fried agreeability that is often associated with abliteration or similar techniques.</div>
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<tr><td>Top-P</td><td>0.95</td></tr>
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<tr><td>Min-P</td><td>0.1 - 0.2</td></tr>
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<tr><td>Adaptive-P Target</td><td style="color: #c6f755;">0.6</td></tr>
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<tr><td>Adaptive-P Decay</td><td style="color: #c6f755;">0.5</td></tr>
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<h3>🪻 GGUF Quants</h3>
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<div style="font-size: 0.9rem; color: #94a3b8; margin-bottom: 15px;">Select your vintage below.</div>
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<thead>
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<tr><th>Quant</th><th style="color: #cbd5e1;">Size</th><th>Link</th></tr>
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<tbody>
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<tr><td>Q4_K_S</td><td style="color: #94a3b8; font-family: monospace; text-align: right;">17.8 GB</td><td><a href="https://huggingface.co/Nimbz/Gemma-4-Giftige-Blume-31B-GGUF/blob/main/Giftige-Blume-31B-v1-Q4_K_S.gguf">Download</a></td></tr>
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<tr><td>Q4_K_M</td><td style="color: #94a3b8; font-family: monospace; text-align: right;">18.7 GB</td><td><a href="https://huggingface.co/Nimbz/Gemma-4-Giftige-Blume-31B-v1-GGUF/blob/main/Giftige-Blume-31B-v1-Q4_K_M.gguf">Download</a></td></tr>
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<tr><td>Q5_K_S</td><td style="color: #94a3b8; font-family: monospace; text-align: right;">21.3 GB</td><td><a href="https://huggingface.co/Nimbz/Gemma-4-Giftige-Blume-31B-v1-GGUF/blob/main/Giftige-Blume-31B-v1-Q5_K_S.gguf">Download</a></td></tr>
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<tr><td>Q5_K_M</td><td style="color: #94a3b8; font-family: monospace; text-align: right;">21.8 GB</td><td><a href="https://huggingface.co/Nimbz/Gemma-4-Giftige-Blume-31B-v1-GGUF/blob/main/Giftige-Blume-31B-v1-Q5_K_M.gguf">Download</a></td></tr>
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<tr><td>Q6_K</td><td style="color: #94a3b8; font-family: monospace; text-align: right;">25.2 GB</td><td><a href="https://huggingface.co/Nimbz/Gemma-4-Giftige-Blume-31B-v1-GGUF/blob/main/Giftige-Blume-31B-v1-Q6_K.gguf">Download</a></td></tr>
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<tr><td>Q8_0</td><td style="color: #94a3b8; font-family: monospace; text-align: right;">32.6 GB</td><td><a href="https://huggingface.co/Nimbz/Gemma-4-Giftige-Blume-31B-v1-GGUF/blob/main/Giftige-Blume-31B-v1-Q8_0.gguf">Download</a></td></tr>
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<div class="flora-card violet-card" style="margin-top: 35px;">
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<h3>📜 Prompt Format</h3>
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<div style="margin-bottom: 15px;"><a href="https://huggingface.co/google/gemma-4-31B-it#2-thinking-mode-configuration" style="color: #f5e872; font-weight: bold; text-decoration: none; border-bottom: 1px dashed #f5e872;">Please refer to the original google/gemma-4-31b-it for the correct chat template.</a></div>
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<div style="color: #cbd5e1;">Let your frontend handle the chat template if possible (e.g., Chat Completion in SillyTavern).</div>
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<div style="background: rgba(0,0,0,0.5); padding: 15px; border-radius: 8px; border-left: 3px solid #c6f755; margin-top: 15px;">
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<strong style="color: #22c55e;">For Reasoning:</strong> Add <code><|think|></code> at the very beginning of the system prompt. Thinking happens between <code><|channel>thought\n</code> and <code><channel|></code> tags.
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<h3>🏵️ 1. Phase</h3>
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<div style="margin-bottom: 15px;"><details>
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<summary>Broad RP Scenario: model_stock</summary>
|
| 224 |
|
| 225 |
-
``
|
| 226 |
-
|
| 227 |
-
|
| 228 |
-
|
| 229 |
-
|
| 230 |
-
|
| 231 |
-
normalize: true
|
| 232 |
-
models:
|
| 233 |
-
- model: ./LatitudeGames/G4-Equinox-31B
|
| 234 |
-
- model: ./MRockatansky/G4-Gemma-4-31B-storymaxxed
|
| 235 |
-
- model: ./MRockatansky/G4-Gemma-4-31B-storymaxxed2
|
| 236 |
-
- model: ./AuriAetherwiing/G4-31B-Musica-v1
|
| 237 |
-
```
|
| 238 |
-
|
| 239 |
-
</details></p>
|
| 240 |
-
</div>
|
| 241 |
-
</div>
|
| 242 |
-
<div class="flora-card">
|
| 243 |
-
<h3>💐 2. Phase</h3>
|
| 244 |
-
<div style="margin-bottom: 15px;"><details>
|
| 245 |
-
<summary>Heretic RP Engine: breadcrumbs_ties</summary>
|
| 246 |
-
|
| 247 |
-
```
|
| 248 |
-
merge_method: breadcrumbs_ties
|
| 249 |
-
base_model: ./Broad-RP-Scenario-model_stock_phase1
|
| 250 |
-
tokenizer_source: base
|
| 251 |
-
dtype: bfloat16
|
| 252 |
-
|
| 253 |
-
modules:
|
| 254 |
-
text_decoder:
|
| 255 |
-
|
| 256 |
-
slices:
|
| 257 |
-
- sources:
|
| 258 |
-
- model: ./Broad-RP-Scenario-model_stock_phase1
|
| 259 |
-
layer_range: [0, 12]
|
| 260 |
-
parameters:
|
| 261 |
-
weight: 0.90
|
| 262 |
-
- model: ./llmfan46/gemma-4-Ortenzya-The-Creative-Wordsmith-31B-it-uncensored-heretic
|
| 263 |
-
layer_range: [0, 12]
|
| 264 |
-
parameters:
|
| 265 |
-
density: 0.35
|
| 266 |
-
weight: 0.30
|
| 267 |
-
|
| 268 |
-
- sources:
|
| 269 |
-
- model: ./Broad-RP-Scenario-model_stock_phase1
|
| 270 |
-
layer_range: [12, 24]
|
| 271 |
-
parameters:
|
| 272 |
-
weight: 0.85
|
| 273 |
-
- model: ./llmfan46/gemma-4-Ortenzya-The-Creative-Wordsmith-31B-it-uncensored-heretic
|
| 274 |
-
layer_range: [12, 24]
|
| 275 |
-
parameters:
|
| 276 |
-
density: 0.15
|
| 277 |
-
weight: 0.15
|
| 278 |
-
- model: /media/nimbz/cold_storage/LLM/WEIGHTS/G4-Mero-Artemis-31B-v0.3.1
|
| 279 |
-
layer_range: [12, 24]
|
| 280 |
-
parameters:
|
| 281 |
-
density: 0.50
|
| 282 |
-
weight: 0.60
|
| 283 |
-
|
| 284 |
-
- sources:
|
| 285 |
-
- model: ./Broad-RP-Scenario-model_stock_phase1
|
| 286 |
-
layer_range: [24, 42]
|
| 287 |
-
parameters:
|
| 288 |
-
weight: 0.80
|
| 289 |
-
- model: ./llmfan46/gemma-4-Ortenzya-The-Creative-Wordsmith-31B-it-uncensored-heretic
|
| 290 |
-
layer_range: [24, 42]
|
| 291 |
-
parameters:
|
| 292 |
-
density: 0.30
|
| 293 |
-
weight: 0.35
|
| 294 |
-
- model: /media/nimbz/cold_storage/LLM/WEIGHTS/G4-Mero-Artemis-31B-v0.3.1
|
| 295 |
-
layer_range: [24, 42]
|
| 296 |
-
parameters:
|
| 297 |
-
density: 0.70
|
| 298 |
-
weight: 0.80
|
| 299 |
-
|
| 300 |
-
- sources:
|
| 301 |
-
- model: ./Broad-RP-Scenario-model_stock_phase1
|
| 302 |
-
layer_range: [42, 54]
|
| 303 |
-
parameters:
|
| 304 |
-
weight: 0.80
|
| 305 |
-
- model: ./llmfan46/gemma-4-Ortenzya-The-Creative-Wordsmith-31B-it-uncensored-heretic
|
| 306 |
-
layer_range: [42, 54]
|
| 307 |
-
parameters:
|
| 308 |
-
density: 0.65
|
| 309 |
-
weight: 0.70
|
| 310 |
-
- model: /media/nimbz/cold_storage/LLM/WEIGHTS/G4-Mero-Artemis-31B-v0.3.1
|
| 311 |
-
layer_range: [42, 54]
|
| 312 |
-
parameters:
|
| 313 |
-
density: 0.40
|
| 314 |
-
weight: 0.45
|
| 315 |
-
|
| 316 |
-
- sources:
|
| 317 |
-
- model: ./Broad-RP-Scenario-model_stock_phase1
|
| 318 |
-
layer_range: [54, 60]
|
| 319 |
-
parameters:
|
| 320 |
-
weight: 0.85
|
| 321 |
-
- model: ./llmfan46/gemma-4-Ortenzya-The-Creative-Wordsmith-31B-it-uncensored-heretic
|
| 322 |
-
layer_range: [54, 60]
|
| 323 |
-
parameters:
|
| 324 |
-
density: 0.75
|
| 325 |
-
weight: 0.85
|
| 326 |
-
|
| 327 |
-
vision_tower:
|
| 328 |
-
models:
|
| 329 |
-
- model: ./Broad-RP-Scenario-model_stock_phase1
|
| 330 |
-
```
|
| 331 |
-
|
| 332 |
-
</details></p>
|
| 333 |
-
</div>
|
| 334 |
-
</div>
|
| 335 |
-
<div class="flora-card">
|
| 336 |
-
<h3>🌳 3. Phase</h3>
|
| 337 |
-
<div style="margin-bottom: 15px;"><details>
|
| 338 |
-
<summary>Logical RP Melting: della_linear</summary>
|
| 339 |
-
|
| 340 |
-
```
|
| 341 |
-
merge_method: della_linear
|
| 342 |
-
base_model: ./google/gemma-4-31B-it
|
| 343 |
-
tokenizer_source: base
|
| 344 |
-
dtype: bfloat16
|
| 345 |
-
parameters:
|
| 346 |
-
epsilon: 0.05
|
| 347 |
-
lambda: 1.0
|
| 348 |
-
normalize: true
|
| 349 |
-
int8_mask: true
|
| 350 |
-
|
| 351 |
-
modules:
|
| 352 |
-
text_decoder:
|
| 353 |
-
slices:
|
| 354 |
-
- sources:
|
| 355 |
-
- model: ./google/gemma-4-31B-it
|
| 356 |
-
layer_range: [0, 12]
|
| 357 |
-
parameters:
|
| 358 |
-
weight: 0.75
|
| 359 |
-
- model: ./p-e-r-e-g-r-i-n-e/Sprinkle-Gemma-4-31B
|
| 360 |
-
layer_range: [0, 12]
|
| 361 |
-
parameters:
|
| 362 |
-
density: 0.15
|
| 363 |
-
weight:
|
| 364 |
-
- filter: embed_tokens
|
| 365 |
-
value: 0.0
|
| 366 |
-
- filter: lm_head
|
| 367 |
-
value: 0.0
|
| 368 |
-
- value: 0.20
|
| 369 |
-
- model: ./Jackrong/Gemopus-4-31B-it
|
| 370 |
-
layer_range: [0, 12]
|
| 371 |
-
parameters:
|
| 372 |
-
density: 0.25
|
| 373 |
-
weight:
|
| 374 |
-
- filter: embed_tokens
|
| 375 |
-
value: 0.0
|
| 376 |
-
- filter: lm_head
|
| 377 |
-
value: 0.0
|
| 378 |
-
- value: 0.25
|
| 379 |
-
- model: ./Heretic-RP-Engine_breadcrumbs_ties
|
| 380 |
-
layer_range: [0, 12]
|
| 381 |
-
parameters:
|
| 382 |
-
density: 0.40
|
| 383 |
-
weight:
|
| 384 |
-
- filter: embed_tokens
|
| 385 |
-
value: 0.0
|
| 386 |
-
- filter: lm_head
|
| 387 |
-
value: 0.0
|
| 388 |
-
- value: 0.50
|
| 389 |
-
|
| 390 |
-
- sources:
|
| 391 |
-
- model: ./google/gemma-4-31B-it
|
| 392 |
-
layer_range: [12, 24]
|
| 393 |
-
parameters:
|
| 394 |
-
weight: 0.75
|
| 395 |
-
- model: ./p-e-r-e-g-r-i-n-e/Sprinkle-Gemma-4-31B
|
| 396 |
-
layer_range: [12, 24]
|
| 397 |
-
parameters:
|
| 398 |
-
density: 0.20
|
| 399 |
-
weight:
|
| 400 |
-
- filter: embed_tokens
|
| 401 |
-
value: 0.0
|
| 402 |
-
- filter: lm_head
|
| 403 |
-
value: 0.0
|
| 404 |
-
- value: 0.25
|
| 405 |
-
- model: ./Jackrong/Gemopus-4-31B-it
|
| 406 |
-
layer_range: [12, 24]
|
| 407 |
-
parameters:
|
| 408 |
-
density: 0.35
|
| 409 |
-
weight:
|
| 410 |
-
- filter: embed_tokens
|
| 411 |
-
value: 0.0
|
| 412 |
-
- filter: lm_head
|
| 413 |
-
value: 0.0
|
| 414 |
-
- value: 0.50
|
| 415 |
-
- model: ./Heretic-RP-Engine_breadcrumbs_ties
|
| 416 |
-
layer_range: [12, 24]
|
| 417 |
-
parameters:
|
| 418 |
-
density: 0.50
|
| 419 |
-
weight:
|
| 420 |
-
- filter: embed_tokens
|
| 421 |
-
value: 0.0
|
| 422 |
-
- filter: lm_head
|
| 423 |
-
value: 0.0
|
| 424 |
-
- value: 0.60
|
| 425 |
-
|
| 426 |
-
- sources:
|
| 427 |
-
- model: ./google/gemma-4-31B-it
|
| 428 |
-
layer_range: [24, 42]
|
| 429 |
-
parameters:
|
| 430 |
-
weight: 0.75
|
| 431 |
-
- model: ./p-e-r-e-g-r-i-n-e/Sprinkle-Gemma-4-31B
|
| 432 |
-
layer_range: [24, 42]
|
| 433 |
-
parameters:
|
| 434 |
-
density: 0.30
|
| 435 |
-
weight:
|
| 436 |
-
- filter: embed_tokens
|
| 437 |
-
value: 0.0
|
| 438 |
-
- filter: lm_head
|
| 439 |
-
value: 0.0
|
| 440 |
-
- value: 0.20
|
| 441 |
-
- model: ./Jackrong/Gemopus-4-31B-it
|
| 442 |
-
layer_range: [24, 42]
|
| 443 |
-
parameters:
|
| 444 |
-
density: 0.65
|
| 445 |
-
weight:
|
| 446 |
-
- filter: embed_tokens
|
| 447 |
-
value: 0.0
|
| 448 |
-
- filter: lm_head
|
| 449 |
-
value: 0.0
|
| 450 |
-
- value: 0.65
|
| 451 |
-
- model: ./Heretic-RP-Engine_breadcrumbs_ties
|
| 452 |
-
layer_range: [24, 42]
|
| 453 |
-
parameters:
|
| 454 |
-
density: 0.85
|
| 455 |
-
weight:
|
| 456 |
-
- filter: embed_tokens
|
| 457 |
-
value: 0.0
|
| 458 |
-
- filter: lm_head
|
| 459 |
-
value: 0.0
|
| 460 |
-
- value: 0.75
|
| 461 |
-
|
| 462 |
-
- sources:
|
| 463 |
-
- model: ./google/gemma-4-31B-it
|
| 464 |
-
layer_range: [42, 54]
|
| 465 |
-
parameters:
|
| 466 |
-
weight: 0.75
|
| 467 |
-
- model: ./p-e-r-e-g-r-i-n-e/Sprinkle-Gemma-4-31B
|
| 468 |
-
layer_range: [42, 54]
|
| 469 |
-
parameters:
|
| 470 |
-
density: 0.25
|
| 471 |
-
weight:
|
| 472 |
-
- filter: embed_tokens
|
| 473 |
-
value: 0.0
|
| 474 |
-
- filter: lm_head
|
| 475 |
-
value: 0.0
|
| 476 |
-
- value: 0.45
|
| 477 |
-
- model: ./Heretic-RP-Engine_breadcrumbs_ties
|
| 478 |
-
layer_range: [42, 54]
|
| 479 |
-
parameters:
|
| 480 |
-
density: 0.40
|
| 481 |
-
weight:
|
| 482 |
-
- filter: embed_tokens
|
| 483 |
-
value: 0.0
|
| 484 |
-
- filter: lm_head
|
| 485 |
-
value: 0.0
|
| 486 |
-
- value: 0.75
|
| 487 |
-
|
| 488 |
-
- sources:
|
| 489 |
-
- model: ./google/gemma-4-31B-it
|
| 490 |
-
layer_range: [54, 60]
|
| 491 |
-
parameters:
|
| 492 |
-
weight: 0.70
|
| 493 |
-
- model: ./p-e-r-e-g-r-i-n-e/Sprinkle-Gemma-4-31B
|
| 494 |
-
layer_range: [54, 60]
|
| 495 |
-
parameters:
|
| 496 |
-
density: 0.25
|
| 497 |
-
weight:
|
| 498 |
-
- filter: embed_tokens
|
| 499 |
-
value: 0.0
|
| 500 |
-
- filter: lm_head
|
| 501 |
-
value: 0.0
|
| 502 |
-
- value: 0.50
|
| 503 |
-
- model: ./Heretic-RP-Engine_breadcrumbs_ties
|
| 504 |
-
layer_range: [54, 60]
|
| 505 |
-
parameters:
|
| 506 |
-
density: 0.35
|
| 507 |
-
weight:
|
| 508 |
-
- filter: embed_tokens
|
| 509 |
-
value: 0.0
|
| 510 |
-
- filter: lm_head
|
| 511 |
-
value: 0.0
|
| 512 |
-
- value: 0.65
|
| 513 |
-
|
| 514 |
-
vision_tower:
|
| 515 |
-
models:
|
| 516 |
-
- model: ./google/gemma-4-31B-it
|
| 517 |
-
```
|
| 518 |
-
|
| 519 |
-
</details></p>
|
| 520 |
-
</div>
|
| 521 |
-
</div>
|
| 522 |
-
</div>
|
| 523 |
-
<div style="position: relative; z-index: 5; margin-top: 40px;">
|
| 524 |
-
<h2 style="color: #c6f755; border-bottom: 1px solid #14532d; padding-bottom: 10px;">🌸 Credits & Honors</h2>
|
| 525 |
-
<div class="flora-card brown-card blume-credits" style="margin-top: 40px;">
|
| 526 |
-
<ul>
|
| 527 |
-
<li><b style="color: #22c55e;">Google DeepMind & The Open-Source Community:</b> For providing the brilliant base model, merges and fine-tunes that made this merge possible.</li>
|
| 528 |
-
<li><b style="color: #22c55e;"><a href="https://www.reddit.com/r/BeaverAI/">The BeaverAI Community</a>:</b> Great people, always supportive, a really nice place to hang around.</li>
|
| 529 |
-
<li><b style="color: #22c55e;">Mergekit:</b> Thank you arcee-ai for the mergekit, thank you zerofata for actually providing Gemma-4 support!</li>
|
| 530 |
-
<li><b style="color: #22c55e;"><a href="https://huggingface.co/Ateron">Ateron</a>:</b> This guy.</li>
|
| 531 |
-
<li><b style="color: #22c55e;">Google Gemini:</b> For hallucinating when I needed it the most.</li>
|
| 532 |
-
</ul>
|
| 533 |
-
</div>
|
|
|
|
| 1 |
---
|
| 2 |
+
base_model: Blazed-Forge/Gemma-4-Giftige-Blume-31B-v1
|
| 3 |
+
library_name: transformers
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|
| 4 |
tags:
|
| 5 |
+
- quantized
|
| 6 |
+
- w8a16
|
| 7 |
+
- fp8
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|
| 8 |
---
|
| 9 |
|
| 10 |
+
# Gemma-4-Giftige-Blume-31B-v1-W8A16-FP8
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|
| 11 |
|
| 12 |
+
Quantized version of [Blazed-Forge/Gemma-4-Giftige-Blume-31B-v1](https://huggingface.co/Blazed-Forge/Gemma-4-Giftige-Blume-31B-v1).
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|
| 13 |
|
| 14 |
+
## Format
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|
| 15 |
|
| 16 |
+
Offline-quantized **W8A16 FP8** in the
|
| 17 |
+
[compressed-tensors](https://github.com/neuralmagic/compressed-tensors)
|
| 18 |
+
`float-quantized` format: weights in `float8_e4m3fn` with per-output-channel
|
| 19 |
+
symmetric scales, activations kept in bf16/fp16.
|
| 20 |
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| 21 |
+
## How it was quantized
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| 22 |
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| 23 |
+
For each linear layer, every output row gets its own scale starting from
|
| 24 |
+
`amax / 448`, refined by an MSE clip search over ~9 clip fractions
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| 25 |
+
(0.8–1.0× amax) picking the lowest-error scale per row. Weights are then
|
| 26 |
+
quantized `q = e4m3(w / scale)` with round-to-nearest and saturation. This
|
| 27 |
+
per-channel + clipping scheme gives better SNR than vLLM's online per-tensor
|
| 28 |
+
`--quantization fp8` path.
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| 29 |
|
| 30 |
+
Only 2D linear projection weights are quantized (attention q/k/v/o, MLP
|
| 31 |
+
gate/up/down). Embeddings, norms, lm_head, routers/experts, and the vision
|
| 32 |
+
tower stay in bf16 and are listed in the checkpoint's `ignore` list, so vLLM
|
| 33 |
+
leaves them untouched.
|
| 34 |
|
| 35 |
+
## Supported vLLM platforms
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| 36 |
|
| 37 |
+
- **Intel XPU** — `XPUW8A16FP8LinearKernel` (the intended target).
|
| 38 |
+
- **NVIDIA CUDA** (SM75+, i.e. Turing and newer) —
|
| 39 |
+
`HummingFP8ScaledMMLinearKernel` when the `humming` package is installed,
|
| 40 |
+
otherwise `MarlinFP8ScaledMMLinearKernel`.
|
| 41 |
+
- **Not supported**: ROCm, CPU, TPU — vLLM has no W8A16-FP8 kernel for these
|
| 42 |
+
backends yet, so loading will fail with a "no kernel" error.
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