Instructions to use CodeHima/TOSRobertaV2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CodeHima/TOSRobertaV2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CodeHima/TOSRobertaV2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CodeHima/TOSRobertaV2") model = AutoModelForSequenceClassification.from_pretrained("CodeHima/TOSRobertaV2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2341e805993c1859fac25f169315cc89922047c82a9588903910bb92d8551719
- Size of remote file:
- 1.42 GB
- SHA256:
- e5a0b22bafae9b54a76117376855452a6aaae37971c29c09ed9983553d39a12c
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