Instructions to use hf-internal-testing/tiny-random-LiltForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LiltForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-LiltForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LiltForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-LiltForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d16f778748549fb28b6eac67d6c661bd8f95fc45aea9186d88c86c6ec30c43f9
- Size of remote file:
- 281 kB
- SHA256:
- b3d139a695030215a2a7202b06ca560881665f98b096ec15bf6b07729ee8133d
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