Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

BMRetriever
/
BMRetriever-410M

Feature Extraction
Transformers
Safetensors
English
gpt_neox
medical
biology
retrieval
LLM
Model card Files Files and versions
xet
Community
1

Instructions to use BMRetriever/BMRetriever-410M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use BMRetriever/BMRetriever-410M with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="BMRetriever/BMRetriever-410M")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("BMRetriever/BMRetriever-410M")
    model = AutoModel.from_pretrained("BMRetriever/BMRetriever-410M")
  • Notebooks
  • Google Colab
  • Kaggle
BMRetriever-410M
1.42 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 17 commits
ritaranx's picture
ritaranx
Update README.md
e3569bf verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    5.51 kB
    Update README.md over 1 year ago
  • config.json
    753 Bytes
    Upload 4 files about 2 years ago
  • model.safetensors
    1.42 GB
    xet
    Upload 4 files about 2 years ago
  • tokenizer.json
    2.31 MB
    Upload 4 files about 2 years ago
  • tokenizer_config.json
    5.22 kB
    Upload 4 files about 2 years ago