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

krm
/
BARTkrame-abstract

Summarization
Transformers
PyTorch
TensorBoard
mbart
text2text-generation
Generated from Trainer
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use krm/BARTkrame-abstract with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use krm/BARTkrame-abstract with Transformers:

    # Use a pipeline as a high-level helper
    # Warning: Pipeline type "summarization" is no longer supported in transformers v5.
    # You must load the model directly (see below) or downgrade to v4.x with:
    # 'pip install "transformers<5.0.0'
    from transformers import pipeline
    
    pipe = pipeline("summarization", model="krm/BARTkrame-abstract")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("krm/BARTkrame-abstract")
    model = AutoModelForSeq2SeqLM.from_pretrained("krm/BARTkrame-abstract")
  • Notebooks
  • Google Colab
  • Kaggle
BARTkrame-abstract / runs
29.9 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
krm's picture
krm
Training good 2
c179b9d over 3 years ago
  • Oct15_01-35-22_e2d80a5d9bd6
    Training good 1 over 3 years ago
  • Oct15_06-02-26_1243a7efd2f2
    Training good 2 over 3 years ago