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yashrane2904
/
LED_Finetuned

Summarization
Transformers
Safetensors
English
led
text2text-generation
Summarization
Longformer
LED
Fine-Tuned
Abstractive
Scientific
seq2seq
english
attention
text-processing
NLP
beam-search
Model card Files Files and versions
xet
Community

Instructions to use yashrane2904/LED_Finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use yashrane2904/LED_Finetuned 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="yashrane2904/LED_Finetuned")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("yashrane2904/LED_Finetuned")
    model = AutoModelForSeq2SeqLM.from_pretrained("yashrane2904/LED_Finetuned")
  • Notebooks
  • Google Colab
  • Kaggle
LED_Finetuned
648 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 14 commits
yashrane2904's picture
yashrane2904
Update README.md
ac8a984 verified about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    3.66 kB
    Update README.md about 2 years ago
  • config.json
    1.14 kB
    Upload LEDForConditionalGeneration about 2 years ago
  • generation_config.json
    133 Bytes
    Upload LEDForConditionalGeneration about 2 years ago
  • model.safetensors
    648 MB
    xet
    Upload LEDForConditionalGeneration about 2 years ago