Instructions to use yuvraj/xSumm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yuvraj/xSumm 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="yuvraj/xSumm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("yuvraj/xSumm") model = AutoModelForSeq2SeqLM.from_pretrained("yuvraj/xSumm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Read announcement at https://discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755 Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/yuvraj/xSumm/README.md6403af6
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