Image-Text-to-Text
Transformers
Safetensors
multilingual
minicpmv
feature-extraction
minicpm-v
vision
ocr
multi-image
video
custom_code
conversational
4-bit precision
gptq
Instructions to use openbmb/MiniCPM-V-2_6-GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openbmb/MiniCPM-V-2_6-GPTQ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="openbmb/MiniCPM-V-2_6-GPTQ", trust_remote_code=True) 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 AutoModel model = AutoModel.from_pretrained("openbmb/MiniCPM-V-2_6-GPTQ", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use openbmb/MiniCPM-V-2_6-GPTQ with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "openbmb/MiniCPM-V-2_6-GPTQ" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "openbmb/MiniCPM-V-2_6-GPTQ", "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/openbmb/MiniCPM-V-2_6-GPTQ
- SGLang
How to use openbmb/MiniCPM-V-2_6-GPTQ 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 "openbmb/MiniCPM-V-2_6-GPTQ" \ --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": "openbmb/MiniCPM-V-2_6-GPTQ", "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 "openbmb/MiniCPM-V-2_6-GPTQ" \ --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": "openbmb/MiniCPM-V-2_6-GPTQ", "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 openbmb/MiniCPM-V-2_6-GPTQ with Docker Model Runner:
docker model run hf.co/openbmb/MiniCPM-V-2_6-GPTQ
| { | |
| "add_prefix_space": false, | |
| "added_tokens_decoder": { | |
| "128244": { | |
| "content": "<unk>", | |
| "lstrip": false, | |
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| "rstrip": false, | |
| "single_word": false, | |
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| "151643": { | |
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| }, | |
| "151644": { | |
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| "151646": { | |
| "content": "<image>", | |
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| "151658": { | |
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| "special": true | |
| }, | |
| "151659": { | |
| "content": "</image_id>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151660": { | |
| "content": "<|reserved_special_token_0|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
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| "151661": { | |
| "content": "<|reserved_special_token_1|>", | |
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| "151662": { | |
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| "151664": { | |
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| "151665": { | |
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| "special": true | |
| } | |
| }, | |
| "additional_special_tokens": [ | |
| "<image>", | |
| "</image>", | |
| "<ref>", | |
| "</ref>", | |
| "<box>", | |
| "</box>", | |
| "<quad>", | |
| "</quad>", | |
| "<point>", | |
| "</point>", | |
| "<slice>", | |
| "</slice>", | |
| "<image_id>", | |
| "</image_id>", | |
| "<|reserved_special_token_0|>", | |
| "<|reserved_special_token_1|>", | |
| "<|reserved_special_token_2|>", | |
| "<|reserved_special_token_3|>", | |
| "<|reserved_special_token_4|>", | |
| "<|reserved_special_token_5|>" | |
| ], | |
| "bos_token": "<|im_start|>", | |
| "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|im_end|>", | |
| "errors": "replace", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<|endoftext|>", | |
| "split_special_tokens": false, | |
| "auto_map": { | |
| "AutoTokenizer": [ | |
| "tokenization_minicpmv_fast.MiniCPMVTokenizerFast", | |
| null | |
| ] | |
| }, | |
| "tokenizer_class": "MiniCPMVTokenizerFast", | |
| "unk_token": "<unk>" | |
| } | |