Instructions to use dtorber/roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dtorber/roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dtorber/roberta-base") model = AutoModelForSequenceClassification.from_pretrained("dtorber/roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dtorber/roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/dtorber/roberta-base/resolve/main/training_args.bin
- Command line
-
hf download hf://dtorber/roberta-base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dtorber/roberta-base/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- d6c6709a3eb6d4d9dc7eaaca0bf28402a1ab30d34cb72b45a629fcf57d44c236
- Size of remote file:
- 4.98 kB
- SHA256:
- a145be7dcfa89d5fb1130248aef74f6bb4bee2e55b242329ad8f4da570711d6d
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