Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Hardware
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

c3ts
/
Newmodel

Text Generation
Transformers
TensorBoard
Safetensors
PEFT
Trained with AutoTrain
text-generation-inference
conversational
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use c3ts/Newmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use c3ts/Newmodel with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="c3ts/Newmodel")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("c3ts/Newmodel", device_map="auto")
  • PEFT

    How to use c3ts/Newmodel with PEFT:

    Task type is invalid.
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use c3ts/Newmodel with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "c3ts/Newmodel"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "c3ts/Newmodel",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/c3ts/Newmodel
  • SGLang

    How to use c3ts/Newmodel 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 "c3ts/Newmodel" \
        --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": "c3ts/Newmodel",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    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 "c3ts/Newmodel" \
            --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": "c3ts/Newmodel",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use c3ts/Newmodel with Docker Model Runner:

    docker model run hf.co/c3ts/Newmodel

You need to agree to share your contact information to access this model

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

Log in or Sign Up to review the conditions and access this model content.

Gated model
You can list files but not access them

Preview of files found in this repository
  • runs
    Upload folder using huggingface_hub over 1 year ago
  • .gitattributes
    1.57 kB
    Upload folder using huggingface_hub over 1 year ago
  • README.md
    1.12 kB
    Upload folder using huggingface_hub over 1 year ago
  • adapter_config.json
    806 Bytes
    Upload folder using huggingface_hub over 1 year ago
  • adapter_model.safetensors
    168 MB
    xet
    Upload folder using huggingface_hub over 1 year ago
  • special_tokens_map.json
    325 Bytes
    Upload folder using huggingface_hub over 1 year ago
  • tokenizer.json
    17.2 MB
    xet
    Upload folder using huggingface_hub over 1 year ago
  • tokenizer_config.json
    55.4 kB
    Upload folder using huggingface_hub over 1 year ago
  • training_args.bin
    5.62 kB
    xet
    Upload folder using huggingface_hub over 1 year ago
  • training_params.json
    1.39 kB
    Upload folder using huggingface_hub over 1 year ago