Instructions to use gustavecortal/roberta_comp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gustavecortal/roberta_comp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gustavecortal/roberta_comp")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gustavecortal/roberta_comp") model = AutoModelForSequenceClassification.from_pretrained("gustavecortal/roberta_comp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gustavecortal/roberta_comp: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/gustavecortal/roberta_comp/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gustavecortal/roberta_comp/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gustavecortal/roberta_comp/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- b690c0b9e7dac1d306ca4995abdf17820887b18e8e5e31290a7755783781c316
- Size of remote file:
- 499 MB
- SHA256:
- 65b5c1f71ab802949eac4cb0646e9ec3b6c9e0a26bada786c58d33bc1496fa6d
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