Instructions to use igandarillas/supcon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use igandarillas/supcon with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="igandarillas/supcon")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("igandarillas/supcon") model = AutoModelForMaskedLM.from_pretrained("igandarillas/supcon", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from igandarillas/supcon: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/igandarillas/supcon/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://igandarillas/supcon/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/igandarillas/supcon/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 9598d352db75a4ee5af6619d638c174dfeeb4647c84a54cd81f5c6cf3367b3be
- Size of remote file:
- 499 MB
- SHA256:
- f7da4efa2107e419b748ba6e6d07908c82ba34a61bdda8d5462c547112c47956
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