Instructions to use mimi/book_data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mimi/book_data with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mimi/book_data") model = AutoModelForSeq2SeqLM.from_pretrained("mimi/book_data", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mimi/book_data: direct link, hf CLI and curl.
- Browser
- Download file 990 MB
-
https://huggingface.co/mimi/book_data/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mimi/book_data/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mimi/book_data/resolve/main/pytorch_model.bin
990 MB
- Xet hash:
- 6c645e30f9dff12178e18121cb807b842b65355fd3f1d86f6a08ea198c65a79e
- Size of remote file:
- 990 MB
- SHA256:
- ebe111c956b1088cd6be9785a2fbf5d9c547f3c5e7252441f152171233e5ab99
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