Instructions to use liamvbetts/bart-base-cnn-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use liamvbetts/bart-base-cnn-v1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("liamvbetts/bart-base-cnn-v1") model = AutoModelForSeq2SeqLM.from_pretrained("liamvbetts/bart-base-cnn-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d1c4a80a16e883576070ed7b196cdd792c618853708eb00caddb7f4050c2ee5
- Size of remote file:
- 4.73 kB
- SHA256:
- 72f0de8cf0d54d4189962b8a07d378252ee4b9ad6bb421a1511542037d051798
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