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:
# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from declare-lab/flan-alpaca-base: direct link, hf CLI and curl.
- Browser
- Download file 990 MB
-
https://huggingface.co/declare-lab/flan-alpaca-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://declare-lab/flan-alpaca-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/declare-lab/flan-alpaca-base/resolve/main/pytorch_model.bin
990 MB
- Xet hash:
- 58375f15b0b96a0507f12fd6c548862f52785793dbdc9a9a209ad8ddff485151
- Size of remote file:
- 990 MB
- SHA256:
- 50f93029d709c57b2464fff16f9553a42c5bc49d4b1c12326d89badfd17c76bb
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