Instructions to use overfly83/test-classification-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use overfly83/test-classification-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="overfly83/test-classification-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("overfly83/test-classification-model") model = AutoModelForSequenceClassification.from_pretrained("overfly83/test-classification-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08e32d2f89561dfd42d384fd8ccc80c2f9d1b2c73b72ab2e8161a29d6ec1f8ee
- Size of remote file:
- 268 MB
- SHA256:
- edf440e080bc5dbdc6fe90280dc6ccaa26a299e7776ebadec5a7c504d723ea23
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