Instructions to use SCS/Fine-tuned-JCSD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SCS/Fine-tuned-JCSD with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("SCS/Fine-tuned-JCSD") model = AutoModelForSeq2SeqLM.from_pretrained("SCS/Fine-tuned-JCSD", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SCS/Fine-tuned-JCSD: direct link, hf CLI and curl.
- Browser
- Download file 1.62 GB
-
https://huggingface.co/SCS/Fine-tuned-JCSD/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SCS/Fine-tuned-JCSD/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SCS/Fine-tuned-JCSD/resolve/main/pytorch_model.bin
1.62 GB
- Xet hash:
- 09d704dade8cecf0fac231def1e96ee36628f8b6809e0e715e9212b3ce8ad597
- Size of remote file:
- 1.62 GB
- SHA256:
- 9255f16b194d23babafcab4cd8a94d25b18fda45611c3d080b5463bcd8f935fb
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