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

  • Log In
  • Sign Up

ChaniM
/
tst-summarization

Summarization
Transformers
PyTorch
TensorBoard
English
pegasus
text2text-generation
Generated from Trainer
Model card Files Files and versions
xet
Metrics Training metrics Community
4

Instructions to use ChaniM/tst-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ChaniM/tst-summarization 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="ChaniM/tst-summarization")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("ChaniM/tst-summarization")
    model = AutoModelForSeq2SeqLM.from_pretrained("ChaniM/tst-summarization")
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Adding `safetensors` variant of this model

#4 opened over 2 years ago by
SFconvertbot

Adding `safetensors` variant of this model

#3 opened over 2 years ago by
SFconvertbot

Adding `safetensors` variant of this model

#2 opened almost 3 years ago by
SFconvertbot
Company
TOS Privacy About Careers
Website
Models Datasets Spaces Pricing Docs