Instructions to use Billyshears/Janus_pro_finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Billyshears/Janus_pro_finetune with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Billyshears/Janus_pro_finetune")# pip install -U transformers accelerate # Load model directly from transformers import MultiModalityCausalLM model = MultiModalityCausalLM.from_pretrained("Billyshears/Janus_pro_finetune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Billyshears/Janus_pro_finetune with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Billyshears/Janus_pro_finetune" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Billyshears/Janus_pro_finetune", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Billyshears/Janus_pro_finetune
- SGLang
How to use Billyshears/Janus_pro_finetune 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 "Billyshears/Janus_pro_finetune" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Billyshears/Janus_pro_finetune", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "Billyshears/Janus_pro_finetune" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Billyshears/Janus_pro_finetune", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Billyshears/Janus_pro_finetune with Docker Model Runner:
docker model run hf.co/Billyshears/Janus_pro_finetune
File size: 334 Bytes
76dc06a | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"add_special_token": false,
"ignore_id": -100,
"image_end_tag": "<end_of_image>",
"image_start_tag": "<begin_of_image>",
"image_tag": "<image_placeholder>",
"mask_prompt": true,
"num_image_tokens": 576,
"pad_tag": "<\uff5c\u2581pad\u2581\uff5c>",
"processor_class": "VLChatProcessor",
"sft_format": "deepseek"
}
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