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:
- 5451c7099d9f5edcd1e8b0213cb79ce5fd6fe9d650e1032099a39f1a0116a77d
- Size of remote file:
- 3.96 kB
- SHA256:
- 5566472723588547d203929cd0b5004d5679a39e463d04f303394479e518993e
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