Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing

  • Log In
  • Sign Up

recursionpharma
/
OpenPhenom

Feature Extraction
Transformers
Safetensors
MAE
custom_code
Model card Files Files and versions
xet
Community
23

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

  • Libraries
  • Transformers

    How to use recursionpharma/OpenPhenom with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="recursionpharma/OpenPhenom", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("recursionpharma/OpenPhenom", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Tensor dimension mismatch in pre-trained model (channel related)

#23 opened 8 days ago by
zuttng

How many total images in the final CAViT-S training dataset (RxRx3 + JUMP-CRISPR/ORF)?

1
#18 opened over 1 year ago by
spud123

JUMP-CP preprocessing

#17 opened over 1 year ago by
jasperhyp

Channel order

1
#16 opened over 1 year ago by
mingyulu
Company
TOS Privacy About Careers
Website
Models Datasets Spaces Pricing Docs