Instructions to use CodeHima/TOSBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CodeHima/TOSBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CodeHima/TOSBert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CodeHima/TOSBert") model = AutoModelForSequenceClassification.from_pretrained("CodeHima/TOSBert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89422502abf1a289c373951adc546f1a7237213a0e44bd9438270f90c437eb3a
- Size of remote file:
- 438 MB
- SHA256:
- e42f3085ec426098f1ccac8a0c489e4738b166bb01e9f6d0237786369cc21b47
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