Instructions to use WHJ1998/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WHJ1998/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="WHJ1998/test_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("WHJ1998/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("WHJ1998/test_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4927940ea2d4182567880bb2e8931fd884dc795e1ea968e5c75b764fcc4a7596
- Size of remote file:
- 46.2 MB
- SHA256:
- c89ac28ef791250d80a0bca6ce7627b06d2bd1d04b115b0d2b21e36870c7bd57
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