Instructions to use SCS/Pre-trained-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SCS/Pre-trained-model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("SCS/Pre-trained-model") model = AutoModelForSeq2SeqLM.from_pretrained("SCS/Pre-trained-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SCS/Pre-trained-model: direct link, hf CLI and curl.
- Browser
- Download file 1.62 GB
-
https://huggingface.co/SCS/Pre-trained-model/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://SCS/Pre-trained-model@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SCS/Pre-trained-model/resolve/refs%2Fpr%2F1/pytorch_model.bin
1.62 GB
- Xet hash:
- 6323cb757d6446b6d613832855d66432d30ebb1552215dbb0286f9c228785d25
- Size of remote file:
- 1.62 GB
- SHA256:
- e7e067966d6ddcc512367403d32079e38658bd8ffe7ca0d744f4db517a23483f
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