Instructions to use bryanhpchiang/test1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bryanhpchiang/test1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bryanhpchiang/test1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bryanhpchiang/test1") model = AutoModelForSequenceClassification.from_pretrained("bryanhpchiang/test1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 86b446445c3bc7e1aecb986fdb516415dc2ec1bb044fd964225e58e2f6bd5141
- Size of remote file:
- 268 MB
- SHA256:
- c0398dbf612ae39764d29f0abc42c6eb752aca852c54850a1605623fa5a7f3e1
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