Instructions to use jimypbr/roberta-base-finetuned-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jimypbr/roberta-base-finetuned-cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jimypbr/roberta-base-finetuned-cola")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jimypbr/roberta-base-finetuned-cola") model = AutoModelForSequenceClassification.from_pretrained("jimypbr/roberta-base-finetuned-cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jimypbr/roberta-base-finetuned-cola: direct link, hf CLI and curl.
- Browser
- Download file 2.8 kB
-
https://huggingface.co/jimypbr/roberta-base-finetuned-cola/resolve/main/training_args.bin
- Command line
-
hf download hf://jimypbr/roberta-base-finetuned-cola/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jimypbr/roberta-base-finetuned-cola/resolve/main/training_args.bin
2.8 kB
- Xet hash:
- 39360e34c2931e58c19e23b44e76ddaa56d6135efc5553e47dee6ed42d1d94a8
- Size of remote file:
- 2.8 kB
- SHA256:
- 9ee9cbe9b5772c3058edd01fa77730a92a8eac99a277b7d7ee8c883e118c807e
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