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star23
/
ba

Text Generation
Transformers
PyTorch
Safetensors
phi-msft
conversational
custom_code
Model card Files Files and versions
xet
Community

Instructions to use star23/ba with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use star23/ba with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="star23/ba", trust_remote_code=True)
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoModelForCausalLM
    model = AutoModelForCausalLM.from_pretrained("star23/ba", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use star23/ba with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "star23/ba"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "star23/ba",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/star23/ba
  • SGLang

    How to use star23/ba 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 "star23/ba" \
        --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": "star23/ba",
    		"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 "star23/ba" \
            --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": "star23/ba",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use star23/ba with Docker Model Runner:

    docker model run hf.co/star23/ba
ba
Ctrl+K
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  • 2 contributors
History: 3 commits
star23's picture
star23
Update README.md
eeb643c verified about 2 years ago
  • configs
    damn about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • LICENSE
    10.1 kB
    damn about 2 years ago
  • README.md
    15 Bytes
    Update README.md about 2 years ago
  • added_tokens.json
    1.13 kB
    damn about 2 years ago
  • config.json
    782 Bytes
    damn about 2 years ago
  • configuration_phi.py
    2.03 kB
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  • generation_config.json
    74 Bytes
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  • merges.txt
    456 kB
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  • model.safetensors.index.json
    25.8 kB
    damn about 2 years ago
  • modeling_phi.py
    34.8 kB
    damn about 2 years ago
  • pytorch_model-00001-of-00002.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.HalfStorage"

    What is a pickle import?

    4.98 GB
    xet
    damn about 2 years ago
  • pytorch_model-00002-of-00002.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.HalfStorage"

    What is a pickle import?

    584 MB
    xet
    damn about 2 years ago
  • pytorch_model.bin.index.json
    24.5 kB
    damn about 2 years ago
  • special_tokens_map.json
    584 Bytes
    damn about 2 years ago
  • tokenizer.json
    2.12 MB
    damn about 2 years ago
  • tokenizer_config.json
    8.04 kB
    damn about 2 years ago
  • vocab.json
    798 kB
    damn about 2 years ago