Instructions to use Jun421/MVP-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jun421/MVP-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, FiDT5 tokenizer = AutoTokenizer.from_pretrained("Jun421/MVP-base") model = FiDT5.from_pretrained("Jun421/MVP-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Jun421/MVP-base: direct link, hf CLI and curl.
- Browser
- Download file 446 MB
-
https://huggingface.co/Jun421/MVP-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Jun421/MVP-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Jun421/MVP-base/resolve/main/pytorch_model.bin
446 MB
- Xet hash:
- cf087367cbb81fd9313f7be20780c004b7394dd5056dbf4e84df413860a5f88d
- Size of remote file:
- 446 MB
- SHA256:
- 83c3b3c06f6945e3786894e75c19c0d157337e953c0f78a64ba64b541c275cb3
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