Instructions to use anuragrawal/flan-t5-base-YT-transcript-sum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anuragrawal/flan-t5-base-YT-transcript-sum with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("anuragrawal/flan-t5-base-YT-transcript-sum") model = AutoModelForSeq2SeqLM.from_pretrained("anuragrawal/flan-t5-base-YT-transcript-sum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bfe9a342b84047e7c7355eba3aa83edddc38b736a7c748f7c5bd93e8b2ce99b0
- Size of remote file:
- 990 MB
- SHA256:
- e74d26c69a52bc6febe593d0720c65b5fc7797ec1954ab625819004352b6c5d0
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