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

  • Log In
  • Sign Up

domsebalj
/
GPcroaT

Text Generation
Transformers
google-tensorflow TensorFlow
Croatian
gpt2
GPT-2
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use domsebalj/GPcroaT with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="domsebalj/GPcroaT")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("domsebalj/GPcroaT")
    model = AutoModelForCausalLM.from_pretrained("domsebalj/GPcroaT")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use domsebalj/GPcroaT with vLLM:

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

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

    How to use domsebalj/GPcroaT with Docker Model Runner:

    docker model run hf.co/domsebalj/GPcroaT
GPcroaT
499 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 13 commits
domsebalj's picture
domsebalj
Update README.md
ffa00e1 over 3 years ago
  • .gitattributes
    1.17 kB
    initial commit almost 4 years ago
  • README.md
    787 Bytes
    Update README.md over 3 years ago
  • config.json
    893 Bytes
    Upload config.json almost 4 years ago
  • merges.txt
    522 kB
    Upload merges.txt almost 4 years ago
  • tf_model.h5
    498 MB
    xet
    Upload tf_model.h5 almost 4 years ago
  • vocab.json
    863 kB
    Upload vocab.json almost 4 years ago