Image-Text-to-Text
Transformers
Safetensors
English
gemma3
unsloth
gemma
google
conversational
text-generation-inference
4-bit precision
bitsandbytes
Instructions to use unsloth/gemma-3-27b-it-bnb-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unsloth/gemma-3-27b-it-bnb-4bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="unsloth/gemma-3-27b-it-bnb-4bit") 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, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("unsloth/gemma-3-27b-it-bnb-4bit") model = AutoModelForImageTextToText.from_pretrained("unsloth/gemma-3-27b-it-bnb-4bit") 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
- vLLM
How to use unsloth/gemma-3-27b-it-bnb-4bit with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "unsloth/gemma-3-27b-it-bnb-4bit" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "unsloth/gemma-3-27b-it-bnb-4bit", "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/unsloth/gemma-3-27b-it-bnb-4bit
- SGLang
How to use unsloth/gemma-3-27b-it-bnb-4bit 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 "unsloth/gemma-3-27b-it-bnb-4bit" \ --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": "unsloth/gemma-3-27b-it-bnb-4bit", "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 "unsloth/gemma-3-27b-it-bnb-4bit" \ --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": "unsloth/gemma-3-27b-it-bnb-4bit", "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" } } ] } ] }' - Unsloth Studio new
How to use unsloth/gemma-3-27b-it-bnb-4bit with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for unsloth/gemma-3-27b-it-bnb-4bit to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for unsloth/gemma-3-27b-it-bnb-4bit to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for unsloth/gemma-3-27b-it-bnb-4bit to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="unsloth/gemma-3-27b-it-bnb-4bit", max_seq_length=2048, ) - Docker Model Runner
How to use unsloth/gemma-3-27b-it-bnb-4bit with Docker Model Runner:
docker model run hf.co/unsloth/gemma-3-27b-it-bnb-4bit
Upload folder using huggingface_hub
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|
| 1219 |
"special": false
|
| 1220 |
},
|
| 1221 |
"152": {
|
| 1222 |
+
"content": "\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581",
|
| 1223 |
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|
| 1224 |
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|
| 1225 |
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|
|
|
|
| 1227 |
"special": false
|
| 1228 |
},
|
| 1229 |
"153": {
|
| 1230 |
+
"content": "\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581",
|
| 1231 |
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|
| 1232 |
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|
| 1233 |
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|
|
|
|
| 1235 |
"special": false
|
| 1236 |
},
|
| 1237 |
"154": {
|
| 1238 |
+
"content": "\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581",
|
| 1239 |
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|
| 1240 |
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|
| 1241 |
"rstrip": false,
|
|
|
|
| 1243 |
"special": false
|
| 1244 |
},
|
| 1245 |
"155": {
|
| 1246 |
+
"content": "\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581",
|
| 1247 |
"lstrip": false,
|
| 1248 |
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|
| 1249 |
"rstrip": false,
|
|
|
|
| 1251 |
"special": false
|
| 1252 |
},
|
| 1253 |
"156": {
|
| 1254 |
+
"content": "\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581",
|
| 1255 |
"lstrip": false,
|
| 1256 |
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|
| 1257 |
"rstrip": false,
|
|
|
|
| 1259 |
"special": false
|
| 1260 |
},
|
| 1261 |
"157": {
|
| 1262 |
+
"content": "\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581",
|
| 1263 |
"lstrip": false,
|
| 1264 |
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|
| 1265 |
"rstrip": false,
|
|
|
|
| 1267 |
"special": false
|
| 1268 |
},
|
| 1269 |
"158": {
|
| 1270 |
+
"content": "\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581",
|
| 1271 |
"lstrip": false,
|
| 1272 |
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|
| 1273 |
"rstrip": false,
|
|
|
|
| 1275 |
"special": false
|
| 1276 |
},
|
| 1277 |
"159": {
|
| 1278 |
+
"content": "\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581",
|
| 1279 |
"lstrip": false,
|
| 1280 |
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|
| 1281 |
"rstrip": false,
|
|
|
|
| 1283 |
"special": false
|
| 1284 |
},
|
| 1285 |
"160": {
|
| 1286 |
+
"content": "\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581",
|
| 1287 |
"lstrip": false,
|
| 1288 |
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|
| 1289 |
"rstrip": false,
|
|
|
|
| 1291 |
"special": false
|
| 1292 |
},
|
| 1293 |
"161": {
|
| 1294 |
+
"content": "\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581",
|
| 1295 |
"lstrip": false,
|
| 1296 |
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|
| 1297 |
"rstrip": false,
|
|
|
|
| 1299 |
"special": false
|
| 1300 |
},
|
| 1301 |
"162": {
|
| 1302 |
+
"content": "\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581",
|
| 1303 |
"lstrip": false,
|
| 1304 |
"normalized": false,
|
| 1305 |
"rstrip": false,
|
|
|
|
| 1307 |
"special": false
|
| 1308 |
},
|
| 1309 |
"163": {
|
| 1310 |
+
"content": "\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581",
|
| 1311 |
"lstrip": false,
|
| 1312 |
"normalized": false,
|
| 1313 |
"rstrip": false,
|
|
|
|
| 1315 |
"special": false
|
| 1316 |
},
|
| 1317 |
"164": {
|
| 1318 |
+
"content": "\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581",
|
| 1319 |
"lstrip": false,
|
| 1320 |
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|
| 1321 |
"rstrip": false,
|
|
|
|
| 1323 |
"special": false
|
| 1324 |
},
|
| 1325 |
"165": {
|
| 1326 |
+
"content": "\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581",
|
| 1327 |
"lstrip": false,
|
| 1328 |
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|
| 1329 |
"rstrip": false,
|
|
|
|
| 1331 |
"special": false
|
| 1332 |
},
|
| 1333 |
"166": {
|
| 1334 |
+
"content": "\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581",
|
| 1335 |
"lstrip": false,
|
| 1336 |
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|
| 1337 |
"rstrip": false,
|
|
|
|
| 1339 |
"special": false
|
| 1340 |
},
|
| 1341 |
"167": {
|
| 1342 |
+
"content": "\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581\u2581",
|
| 1343 |
"lstrip": false,
|
| 1344 |
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|
| 1345 |
"rstrip": false,
|
|
|
|
| 51344 |
"tokenizer_class": "GemmaTokenizer",
|
| 51345 |
"unk_token": "<unk>",
|
| 51346 |
"use_default_system_prompt": false
|
| 51347 |
+
}
|