Image-Text-to-Text
Transformers
Safetensors
multilingual
minicpmv
feature-extraction
minicpm-v
vision
ocr
multi-image
video
custom_code
conversational
Instructions to use newtechdevng/MiniCPM-V-4_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use newtechdevng/MiniCPM-V-4_5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="newtechdevng/MiniCPM-V-4_5", 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("newtechdevng/MiniCPM-V-4_5", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use newtechdevng/MiniCPM-V-4_5 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "newtechdevng/MiniCPM-V-4_5" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "newtechdevng/MiniCPM-V-4_5", "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/newtechdevng/MiniCPM-V-4_5
- SGLang
How to use newtechdevng/MiniCPM-V-4_5 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 "newtechdevng/MiniCPM-V-4_5" \ --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": "newtechdevng/MiniCPM-V-4_5", "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 "newtechdevng/MiniCPM-V-4_5" \ --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": "newtechdevng/MiniCPM-V-4_5", "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 newtechdevng/MiniCPM-V-4_5 with Docker Model Runner:
docker model run hf.co/newtechdevng/MiniCPM-V-4_5
| { | |
| "image_processor_type": "MiniCPMVImageProcessor", | |
| "auto_map": { | |
| "AutoProcessor": "processing_minicpmv.MiniCPMVProcessor", | |
| "AutoImageProcessor": "image_processing_minicpmv.MiniCPMVImageProcessor" | |
| }, | |
| "processor_class": "MiniCPMVProcessor", | |
| "max_slice_nums": 9, | |
| "scale_resolution": 448, | |
| "patch_size": 14, | |
| "use_image_id": true, | |
| "image_feature_size": 64, | |
| "im_start": "<image>", | |
| "im_end": "</image>", | |
| "slice_start": "<slice>", | |
| "slice_end": "</slice>", | |
| "unk": "<unk>", | |
| "im_id_start": "<image_id>", | |
| "im_id_end": "</image_id>", | |
| "slice_mode": true, | |
| "norm_mean": [0.5, 0.5, 0.5], | |
| "norm_std": [0.5, 0.5, 0.5], | |
| "version": 2.6 | |
| } |