Instructions to use a5u7/roberta_t3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use a5u7/roberta_t3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="a5u7/roberta_t3")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("a5u7/roberta_t3") model = AutoModel.from_pretrained("a5u7/roberta_t3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad97d86247f467517692405daae0ad317556e31049eee6e43119134f975ed7d7
- Size of remote file:
- 243 MB
- SHA256:
- 3e030c89aae09631c3558ca347e3473fbc2b18e046d9dbdc204f493853f1a788
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