Instructions to use hsge/TESS_768_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hsge/TESS_768_v1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hsge/TESS_768_v1") model = AutoModel.from_pretrained("hsge/TESS_768_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hsge/TESS_768_v1: direct link, hf CLI and curl.
- Browser
- Download file 255 MB
-
https://huggingface.co/hsge/TESS_768_v1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hsge/TESS_768_v1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hsge/TESS_768_v1/resolve/main/pytorch_model.bin
255 MB
- Xet hash:
- 1a295c059d21aad4a58e1fa65ea4224c6b6578a33f7625e0569887532d634d7f
- Size of remote file:
- 255 MB
- SHA256:
- 892e326a763e00bcb3b9e4c96fb4b0b847a8cb89b77d13982532746fdc688b40
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