Image-Text-to-Text
Transformers
Safetensors
English
qwen2_5_vl
multimodal
unsloth
conversational
text-generation-inference
4-bit precision
bitsandbytes
Instructions to use unsloth/Qwen2.5-VL-32B-Instruct-unsloth-bnb-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unsloth/Qwen2.5-VL-32B-Instruct-unsloth-bnb-4bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="unsloth/Qwen2.5-VL-32B-Instruct-unsloth-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, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("unsloth/Qwen2.5-VL-32B-Instruct-unsloth-bnb-4bit") model = AutoModelForMultimodalLM.from_pretrained("unsloth/Qwen2.5-VL-32B-Instruct-unsloth-bnb-4bit", 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 unsloth/Qwen2.5-VL-32B-Instruct-unsloth-bnb-4bit with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "unsloth/Qwen2.5-VL-32B-Instruct-unsloth-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/Qwen2.5-VL-32B-Instruct-unsloth-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/Qwen2.5-VL-32B-Instruct-unsloth-bnb-4bit
- SGLang
How to use unsloth/Qwen2.5-VL-32B-Instruct-unsloth-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/Qwen2.5-VL-32B-Instruct-unsloth-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/Qwen2.5-VL-32B-Instruct-unsloth-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/Qwen2.5-VL-32B-Instruct-unsloth-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/Qwen2.5-VL-32B-Instruct-unsloth-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 Desktop
- Docker Model Runner
How to use unsloth/Qwen2.5-VL-32B-Instruct-unsloth-bnb-4bit with Docker Model Runner:
docker model run hf.co/unsloth/Qwen2.5-VL-32B-Instruct-unsloth-bnb-4bit
Add files using upload-large-folder tool
Browse files- README.md +4 -18
- chat_template.jinja +7 -0
- config.json +82 -39
- generation_config.json +2 -2
- model-00001-of-00005.safetensors +2 -2
- model-00002-of-00005.safetensors +2 -2
- model-00003-of-00005.safetensors +2 -2
- model-00004-of-00005.safetensors +2 -2
- model-00005-of-00005.safetensors +2 -2
- model.safetensors.index.json +448 -483
- tokenizer_config.json +4 -4
README.md
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---
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base_model:
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license: apache-2.0
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language:
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- en
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pipeline_tag: image-text-to-text
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tags:
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- multimodal
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library_name: transformers
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---
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<strong>See <a href="https://huggingface.co/collections/unsloth/qwen25-vl-all-versions-679ca6c784fad5bd976a05a1">our collection</a> for versions of Qwen2.5-VL including 4-bit & dynamic formats.</strong>
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<a href="https://docs.unsloth.ai/">
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# Qwen2.5-VL-32B-Instruct
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<a href="https://chat.qwenlm.ai/" target="_blank" style="margin: 2px;">
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We enhance both training and inference speeds by strategically implementing window attention into the ViT. The ViT architecture is further optimized with SwiGLU and RMSNorm, aligning it with the structure of the Qwen2.5 LLM.
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We have
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---
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- Qwen/Qwen2.5-VL-32B-Instruct
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license: apache-2.0
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language:
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- en
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pipeline_tag: image-text-to-text
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tags:
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- multimodal
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- unsloth
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library_name: transformers
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---
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# Qwen2.5-VL-32B-Instruct
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<a href="https://chat.qwenlm.ai/" target="_blank" style="margin: 2px;">
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We enhance both training and inference speeds by strategically implementing window attention into the ViT. The ViT architecture is further optimized with SwiGLU and RMSNorm, aligning it with the structure of the Qwen2.5 LLM.
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We have four models with 3, 7, 32 and 72 billion parameters. This repo contains the instruction-tuned 32B Qwen2.5-VL model. For more information, visit our [Blog](https://qwenlm.github.io/blog/qwen2.5-vl/) and [GitHub](https://github.com/QwenLM/Qwen2.5-VL).
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chat_template.jinja
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{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system
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You are a helpful assistant.<|im_end|>
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{% endif %}<|im_start|>{{ message['role'] }}
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{% if message['content'] is string %}{{ message['content'] }}<|im_end|>
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{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>
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{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant
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{% endif %}
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config.json
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"image_token_id": 151655,
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"initializer_range": 0.02,
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"intermediate_size": 27648,
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},
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"tie_word_embeddings": false,
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"in_channels": 3,
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"intermediate_size": 3456,
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"model_type": "qwen2_5_vl",
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"num_heads": 16,
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"image_token_id": 151655,
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"initializer_range": 0.02,
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2830 |
"model.layers.8.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2831 |
"model.layers.8.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
|
| 2832 |
"model.layers.8.self_attn.k_proj.bias": "model-00002-of-00005.safetensors",
|
| 2833 |
"model.layers.8.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
|
tokenizer_config.json
CHANGED
|
@@ -195,16 +195,16 @@
|
|
| 195 |
"<|video_pad|>"
|
| 196 |
],
|
| 197 |
"bos_token": null,
|
| 198 |
-
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
|
| 199 |
"clean_up_tokenization_spaces": false,
|
| 200 |
"eos_token": "<|im_end|>",
|
| 201 |
"errors": "replace",
|
| 202 |
"extra_special_tokens": {},
|
| 203 |
-
"model_max_length":
|
| 204 |
"pad_token": "<|vision_pad|>",
|
| 205 |
"padding_side": "left",
|
| 206 |
"processor_class": "Qwen2_5_VLProcessor",
|
| 207 |
"split_special_tokens": false,
|
| 208 |
"tokenizer_class": "Qwen2Tokenizer",
|
| 209 |
-
"unk_token": null
|
| 210 |
-
}
|
|
|
|
|
|
| 195 |
"<|video_pad|>"
|
| 196 |
],
|
| 197 |
"bos_token": null,
|
|
|
|
| 198 |
"clean_up_tokenization_spaces": false,
|
| 199 |
"eos_token": "<|im_end|>",
|
| 200 |
"errors": "replace",
|
| 201 |
"extra_special_tokens": {},
|
| 202 |
+
"model_max_length": 128000,
|
| 203 |
"pad_token": "<|vision_pad|>",
|
| 204 |
"padding_side": "left",
|
| 205 |
"processor_class": "Qwen2_5_VLProcessor",
|
| 206 |
"split_special_tokens": false,
|
| 207 |
"tokenizer_class": "Qwen2Tokenizer",
|
| 208 |
+
"unk_token": null,
|
| 209 |
+
"chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n{% endif %}<|im_start|>{{ message['role'] }}\n{% if message['content'] is string %}{{ message['content'] }}<|im_end|>\n{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>\n{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}"
|
| 210 |
+
}
|