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ManishThota
/
CustomModel

Text Generation
Transformers
PyTorch
Safetensors
English
Sparrow
endpoints
text-generation-inference
custom_code
Model card Files Files and versions
xet
Community
6

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

  • Libraries
  • Transformers

    How to use ManishThota/CustomModel with Transformers:

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

    How to use ManishThota/CustomModel with vLLM:

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

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

    How to use ManishThota/CustomModel with Docker Model Runner:

    docker model run hf.co/ManishThota/CustomModel
CustomModel
12.8 GB
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  • 2 contributors
History: 47 commits
ManishThota's picture
ManishThota
Update README.md
032bbcb verified about 2 years ago
  • .ipynb_checkpoints
    adding files about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    1.76 kB
    Update README.md about 2 years ago
  • README_old.md
    2.41 kB
    Rename README.md to README_old.md about 2 years ago
  • added_tokens.json
    1.12 kB
    adding files about 2 years ago
  • config.json
    1.72 kB
    Update config.json about 2 years ago
  • configuration_imp.py
    6.54 kB
    Update configuration_imp.py about 2 years ago
  • generation_config.json
    119 Bytes
    adding files about 2 years ago
  • merges.txt
    456 kB
    adding files about 2 years ago
  • model.safetensors
    6.37 GB
    xet
    Adding `safetensors` variant of this model (#5) about 2 years ago
  • modeling_imp.py
    47.9 kB
    Rename modeling_phi.py to modeling_imp.py about 2 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    6.37 GB
    xet
    Upload ImpForCausalLM about 2 years ago
  • special_tokens_map.json
    90 Bytes
    adding files about 2 years ago
  • tokenizer.json
    2.12 MB
    Upload tokenizer about 2 years ago
  • tokenizer_config.json
    8.18 kB
    adding files about 2 years ago
  • vision_encoder.py
    23.6 kB
    Upload ImpForCausalLM about 2 years ago
  • vocab.json
    798 kB
    Upload tokenizer about 2 years ago