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IndexTeam
/
Index-1.9B-Pure

Text Generation
Transformers
PyTorch
index
custom_code
Model card Files Files and versions
xet
Community
1

Instructions to use IndexTeam/Index-1.9B-Pure with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use IndexTeam/Index-1.9B-Pure with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="IndexTeam/Index-1.9B-Pure", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForCausalLM
    model = AutoModelForCausalLM.from_pretrained("IndexTeam/Index-1.9B-Pure", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use IndexTeam/Index-1.9B-Pure with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "IndexTeam/Index-1.9B-Pure"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "IndexTeam/Index-1.9B-Pure",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/IndexTeam/Index-1.9B-Pure
  • SGLang

    How to use IndexTeam/Index-1.9B-Pure 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 "IndexTeam/Index-1.9B-Pure" \
        --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": "IndexTeam/Index-1.9B-Pure",
    		"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 "IndexTeam/Index-1.9B-Pure" \
            --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": "IndexTeam/Index-1.9B-Pure",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use IndexTeam/Index-1.9B-Pure with Docker Model Runner:

    docker model run hf.co/IndexTeam/Index-1.9B-Pure
Index-1.9B-Pure
4.35 GB
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  • 3 contributors
History: 7 commits
AsirAsir's picture
AsirAsir
Update config.json
545a7cb verified almost 2 years ago
  • .gitattributes
    1.57 kB
    init almost 2 years ago
  • LICENSE
    11.7 kB
    init almost 2 years ago
  • README.md
    3.13 kB
    Update README.md almost 2 years ago
  • README_zh.md
    2.84 kB
    Upload 2 files almost 2 years ago
  • config.json
    854 Bytes
    Update config.json almost 2 years ago
  • configuration_index.py
    8.8 kB
    init almost 2 years ago
  • generation_config.json
    125 Bytes
    init almost 2 years ago
  • modeling_index.py
    46.9 kB
    init almost 2 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch.BFloat16Storage",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    4.35 GB
    xet
    init almost 2 years ago
  • special_tokens_map.json
    414 Bytes
    init almost 2 years ago
  • tokenization_index.py
    10.2 kB
    init almost 2 years ago
  • tokenizer.model
    1.01 MB
    xet
    init almost 2 years ago
  • tokenizer_config.json
    1.03 kB
    init almost 2 years ago