Summarization
Transformers
Safetensors
English
led
text2text-generation
Summarization
Longformer
LED
Fine-Tuned
Abstractive
Scientific
seq2seq
english
attention
text-processing
NLP
beam-search
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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("yashrane2904/LED_Finetuned") model = AutoModelForSeq2SeqLM.from_pretrained("yashrane2904/LED_Finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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