Image-Text-to-Text
Transformers
Safetensors
OpenVINO
English
minicpmo
feature-extraction
multimodal
vision-language
optimum-intel
testing
tiny-model
conversational
custom_code
Instructions to use hrithik-dev8/tiny-random-MiniCPM-o-2_6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hrithik-dev8/tiny-random-MiniCPM-o-2_6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="hrithik-dev8/tiny-random-MiniCPM-o-2_6", 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("hrithik-dev8/tiny-random-MiniCPM-o-2_6", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use hrithik-dev8/tiny-random-MiniCPM-o-2_6 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "hrithik-dev8/tiny-random-MiniCPM-o-2_6" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hrithik-dev8/tiny-random-MiniCPM-o-2_6", "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/hrithik-dev8/tiny-random-MiniCPM-o-2_6
- SGLang
How to use hrithik-dev8/tiny-random-MiniCPM-o-2_6 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 "hrithik-dev8/tiny-random-MiniCPM-o-2_6" \ --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": "hrithik-dev8/tiny-random-MiniCPM-o-2_6", "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 "hrithik-dev8/tiny-random-MiniCPM-o-2_6" \ --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": "hrithik-dev8/tiny-random-MiniCPM-o-2_6", "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 hrithik-dev8/tiny-random-MiniCPM-o-2_6 with Docker Model Runner:
docker model run hf.co/hrithik-dev8/tiny-random-MiniCPM-o-2_6
| { | |
| "<unk>": 4900, | |
| "<|endoftext|>": 4901, | |
| "<|im_start|>": 4902, | |
| "<|im_end|>": 4903, | |
| "<|object_ref_start|>": 4904, | |
| "<|object_ref_end|>": 4905, | |
| "<|box_start|>": 4906, | |
| "<|box_end|>": 4907, | |
| "<|quad_start|>": 4908, | |
| "<|quad_end|>": 4909, | |
| "<|vision_start|>": 4910, | |
| "<|vision_end|>": 4911, | |
| "<|vision_pad|>": 4912, | |
| "<|image_pad|>": 4913, | |
| "<|video_pad|>": 4914, | |
| "<image>": 4915, | |
| "</image>": 4916, | |
| "<ref>": 4917, | |
| "</ref>": 4918, | |
| "<box>": 4919, | |
| "</box>": 4920, | |
| "<quad>": 4921, | |
| "</quad>": 4922, | |
| "<point>": 4923, | |
| "</point>": 4924, | |
| "<slice>": 4925, | |
| "</slice>": 4926, | |
| "<image_id>": 4927, | |
| "</image_id>": 4928, | |
| "<unit>": 4929, | |
| "</unit>": 4930, | |
| "<asr>": 4931, | |
| "</asr>": 4932, | |
| "<query>": 4933, | |
| "</query>": 4934, | |
| "<|audio_start|>": 4935, | |
| "<|audio|>": 4936, | |
| "<|audio_end|>": 4937, | |
| "<|spk_bos|>": 4938, | |
| "<|spk|>": 4939, | |
| "<|spk_eos|>": 4940, | |
| "<|tts_bos|>": 4941, | |
| "<|tts_eos|>": 4942, | |
| "<|listen|>": 4943, | |
| "<|speak|>": 4944, | |
| "<|interrupt|>": 4945, | |
| "<|vad_start|>": 4946, | |
| "<|vad_end|>": 4947, | |
| "<reserved_43>": 4948, | |
| "<reserved_53>": 4949 | |
| } |