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

Rostlab
/
prot_t5_xxl_bfd

Feature Extraction
Transformers
PyTorch
t5
Model card Files Files and versions
xet
Community
1

Instructions to use Rostlab/prot_t5_xxl_bfd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Rostlab/prot_t5_xxl_bfd with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="Rostlab/prot_t5_xxl_bfd")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("Rostlab/prot_t5_xxl_bfd")
    model = AutoModel.from_pretrained("Rostlab/prot_t5_xxl_bfd")
  • Notebooks
  • Google Colab
  • Kaggle
prot_t5_xxl_bfd
45.1 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
Ahmed Elnaggar
add t5-xl model
34a4208 over 5 years ago
  • .gitattributes
    345 Bytes
    initial commit over 5 years ago
  • config.json
    476 Bytes
    add t5-xl model over 5 years ago
  • pytorch_model.bin
    45.1 GB
    xet
    add t5-xl model over 5 years ago
  • special_tokens_map.json
    1.79 kB
    add t5-xl model over 5 years ago
  • spiece.model
    238 kB
    add t5-xl model over 5 years ago
  • tokenizer_config.json
    24 Bytes
    add t5-xl model over 5 years ago