Instructions to use nics-efc/C2C_Fuser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nics-efc/C2C_Fuser with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="nics-efc/C2C_Fuser")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nics-efc/C2C_Fuser", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use nics-efc/C2C_Fuser with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "nics-efc/C2C_Fuser" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nics-efc/C2C_Fuser", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/nics-efc/C2C_Fuser
- SGLang
How to use nics-efc/C2C_Fuser 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 "nics-efc/C2C_Fuser" \ --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": "nics-efc/C2C_Fuser", "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 "nics-efc/C2C_Fuser" \ --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": "nics-efc/C2C_Fuser", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use nics-efc/C2C_Fuser with Docker Model Runner:
docker model run hf.co/nics-efc/C2C_Fuser
Commit History
-
Add `library_name` and sample usage to model card
Verified signatureThis PR enhances the model card by: - Adding the `library_name: transformers` metadata tag to enable the automated "How to use" widget on the Hugging Face Hub, as evidenced by the model's reliance on `transformers.AutoModelForCausalLM` and `tokenizer` functionalities. - Including a "Sample Usage" section with a Python code snippet directly from the official GitHub repository's `README.md`, making it easier for users to get started with the model. The snippet has been slightly adjusted to explicitly import `AutoTokenizer` for clarity. Please review and merge if these improvements align with your expectations.0fbafe3
-
Update README.md
Verified signature6d97f8f -
upload 0.6+4_base fuser
Zihan Min6342c7b -
upload 0.6+llama fuser
Zihan Min1e55ac0 -
upload 0.6+0.5 fuser
Zihan Min8704f55 -
Upload folder using huggingface_hub
Verified signaturefb1e189 -
Update README.md
Verified signatured6b5953 -
Update README.md
Verified signaturef21ae6c -
Update README.md
Verified signaturefae6392 -
Update README.md
Verified signature01e800d -
initial commit
Verified signature2b62b89