Instructions to use declare-lab/flan-alpaca-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use declare-lab/flan-alpaca-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("declare-lab/flan-alpaca-base") model = AutoModelForSeq2SeqLM.from_pretrained("declare-lab/flan-alpaca-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a08b65c191ea2a4062efb511a70f575cb0963ef457658081d3aba3b6f743e2c6
- Size of remote file:
- 990 MB
- SHA256:
- 7aae060f8958ea61545d49c550788b67b7973610dc63b14aa802fb52b5ba0e29
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