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Marks-lab
/
LOL-EVE

Text Generation
Transformers
PyTorch
loleve
genomics
dna
language-model
causal-lm
biology
sequence-modeling
variant-prediction
promoter
indel
eqtl
custom_code
Model card Files Files and versions
xet
Community

Instructions to use Marks-lab/LOL-EVE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Marks-lab/LOL-EVE with Transformers:

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

    How to use Marks-lab/LOL-EVE with vLLM:

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

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

    How to use Marks-lab/LOL-EVE with Docker Model Runner:

    docker model run hf.co/Marks-lab/LOL-EVE
LOL-EVE
2.73 GB
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  • 1 contributor
History: 45 commits
cshearer's picture
cshearer
Update Training Data
397bbb8 verified 8 months ago
  • .gitattributes
    1.52 kB
    initial commit 9 months ago
  • README.md
    6.46 kB
    Update Training Data 8 months ago
  • config.json
    804 Bytes
    Upload folder using huggingface_hub 8 months ago
  • example_usage.py
    2.21 kB
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  • gene_embeddings_v4.npz

    Pickle imports

    • No problematic imports detected

    What is a pickle import?

    95.7 MB
    xet
    Upload folder using huggingface_hub 8 months ago
  • modeling_loleve.py
    4.92 kB
    Upload folder using huggingface_hub 8 months ago
  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    2.63 GB
    xet
    Upload LOL-EVE production model v1.0 - adaptive embedding refactor 9 months ago
  • requirements.txt
    71 Bytes
    Upload folder using huggingface_hub 8 months ago
  • special_tokens_map.json
    147 Bytes
    Upload LOL-EVE production model v1.0 - adaptive embedding refactor 9 months ago
  • tokenizer.json
    3.57 MB
    Upload LOL-EVE production model v1.0 - adaptive embedding refactor 9 months ago
  • tokenizer_config.json
    3.37 MB
    Upload LOL-EVE production model v1.0 - adaptive embedding refactor 9 months ago