Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing

  • Log In
  • Sign Up

hpyapali
/
tinyllama-workout

Text Generation
Transformers
Safetensors
tinyllama
Model card Files Files and versions
xet
Community

Instructions to use hpyapali/tinyllama-workout with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use hpyapali/tinyllama-workout with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="hpyapali/tinyllama-workout")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("hpyapali/tinyllama-workout", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use hpyapali/tinyllama-workout with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "hpyapali/tinyllama-workout"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "hpyapali/tinyllama-workout",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/hpyapali/tinyllama-workout
  • SGLang

    How to use hpyapali/tinyllama-workout 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 "hpyapali/tinyllama-workout" \
        --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": "hpyapali/tinyllama-workout",
    		"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 "hpyapali/tinyllama-workout" \
            --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": "hpyapali/tinyllama-workout",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use hpyapali/tinyllama-workout with Docker Model Runner:

    docker model run hf.co/hpyapali/tinyllama-workout

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
  • checkpoint-4
    Add Git LFS tracking about 1 year ago
  • checkpoint-6
    Add Git LFS tracking about 1 year ago
  • --- tags: - transformers - tinyllama - text-generation library_name: transformers ---
    92 Bytes
    Rename README.md to --- tags: - transformers - tinyllama - text-generation library_name: transformers --- about 1 year ago
  • .gitattributes
    140 Bytes
    Upload export.xml about 1 year ago
  • README.md
    216 Bytes
    Update README.md about 1 year ago
  • config.json
    732 Bytes
    xet
    Add Git LFS tracking about 1 year ago
  • export.xml
    190 MB
    xet
    Upload export.xml about 1 year ago
  • generation_config.json
    124 Bytes
    xet
    Add Git LFS tracking about 1 year ago
  • model.safetensors
    2.2 GB
    xet
    Add Git LFS tracking about 1 year ago
  • special_tokens_map.json
    551 Bytes
    xet
    Add Git LFS tracking about 1 year ago
  • tokenizer.json
    3.62 MB
    xet
    Add Git LFS tracking about 1 year ago
  • tokenizer_config.json
    1.4 kB
    xet
    Add Git LFS tracking about 1 year ago