Instructions to use CodeHima/Tos-Roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CodeHima/Tos-Roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CodeHima/Tos-Roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CodeHima/Tos-Roberta") model = AutoModelForSequenceClassification.from_pretrained("CodeHima/Tos-Roberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ca25020f94c623effa6f1e12d4b688c9fc1e0b7591129897d1b4188f0716c90
- Size of remote file:
- 1.42 GB
- SHA256:
- f5b7258e1b28f285e873a0a2cb8bc79dd913e8330fbe9b6772d181a7e07f5ef0
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