Instructions to use demdecuong/stroke_sup_simcse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use demdecuong/stroke_sup_simcse with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="demdecuong/stroke_sup_simcse")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("demdecuong/stroke_sup_simcse") model = AutoModel.from_pretrained("demdecuong/stroke_sup_simcse", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from demdecuong/stroke_sup_simcse: direct link, hf CLI and curl.
- Browser
- Download file 2.1 kB
-
https://huggingface.co/demdecuong/stroke_sup_simcse/resolve/main/training_args.bin
- Command line
-
hf download hf://demdecuong/stroke_sup_simcse/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/demdecuong/stroke_sup_simcse/resolve/main/training_args.bin
2.1 kB
- Xet hash:
- dca83107fdca326870e18830191b084509bb993ad826992f3212851c504205da
- Size of remote file:
- 2.1 kB
- SHA256:
- ce75296748a079cfb523332bd12778a99b532e48fc8b97a5383cb39780b6b4b1
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