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eye1patch
/
merlin

Text Generation
Transformers
PyTorch
Merlin
English
electromagnetic-signals
multimodal-llm
iq-signals
low-snr
conversational
Model card Files Files and versions
xet
Community

Instructions to use eye1patch/merlin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use eye1patch/merlin with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="eye1patch/merlin")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("eye1patch/merlin", dtype="auto")
  • Merlin

    How to use eye1patch/merlin with Merlin:

    # No code snippets available yet for this library.
    
    # To use this model, check the repository files and the library's documentation.
    
    # Want to help? PRs adding snippets are welcome at:
    # https://github.com/huggingface/huggingface.js
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use eye1patch/merlin with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "eye1patch/merlin"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "eye1patch/merlin",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/eye1patch/merlin
  • SGLang

    How to use eye1patch/merlin 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 "eye1patch/merlin" \
        --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": "eye1patch/merlin",
    		"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 "eye1patch/merlin" \
            --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": "eye1patch/merlin",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use eye1patch/merlin with Docker Model Runner:

    docker model run hf.co/eye1patch/merlin
merlin
8.44 GB
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  • 1 contributor
History: 3 commits
eye1patch's picture
eye1patch
Update README.md
371607a verified 3 days ago
  • .gitattributes
    1.52 kB
    initial commit 3 days ago
  • README.md
    4.2 kB
    Update README.md 3 days ago
  • added_tokens.json
    771 Bytes
    upload merlinl 3 days ago
  • chat_template.jinja
    4.04 kB
    upload merlinl 3 days ago
  • merges.txt
    1.67 MB
    upload merlinl 3 days ago
  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    8.44 GB
    xet
    upload merlinl 3 days ago
  • tokenizer_config.json
    5.69 kB
    upload merlinl 3 days ago
  • vocab.json
    3.38 MB
    upload merlinl 3 days ago