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

dflcmu
/
fine_tune_spatial

Question Answering
Transformers
PyTorch
TensorBoard
roberta
Model card Files Files and versions
xet
Metrics Training metrics Community
1

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

  • Libraries
  • Transformers

    How to use dflcmu/fine_tune_spatial with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("question-answering", model="dflcmu/fine_tune_spatial")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForQuestionAnswering
    
    tokenizer = AutoTokenizer.from_pretrained("dflcmu/fine_tune_spatial")
    model = AutoModelForQuestionAnswering.from_pretrained("dflcmu/fine_tune_spatial")
  • Notebooks
  • Google Colab
  • Kaggle
fine_tune_spatial / runs
10.3 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
dflcmu's picture
dflcmu
Training in progress, epoch 0
aae0b80 about 3 years ago
  • Mar26_06-11-00_bc44e3e761a9
    Training in progress, epoch 0 about 3 years ago