Instructions to use QQhahaha/Summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use QQhahaha/Summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("QQhahaha/Summarization") model = AutoModelForSeq2SeqLM.from_pretrained("QQhahaha/Summarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5684f412d913e005c160e4ad89148e537e0c4a100b9f1efa1b66dcdbb7e01479
- Size of remote file:
- 16.3 MB
- SHA256:
- 962ff7570fd5e96d6af4a09008a269437c7933289162dca163a4dd92e2c4502a
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