Instructions to use ModelTC/roberta-base-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/roberta-base-cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/roberta-base-cola")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/roberta-base-cola") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/roberta-base-cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ModelTC/roberta-base-cola: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/ModelTC/roberta-base-cola/resolve/main/training_args.bin
- Command line
-
hf download hf://ModelTC/roberta-base-cola/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ModelTC/roberta-base-cola/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- 19be69c3baa1e5064db0ec20cfa5d68ab8c32255e9c3f87c063530e5cf2f965c
- Size of remote file:
- 3.06 kB
- SHA256:
- a6a9ec72ff30398a3a57fb04827f755f976ef3eeef2f302dbe4134bc1a0ae726
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