Instructions to use hf-internal-testing/tiny-random-TransfoXLForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-TransfoXLForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-TransfoXLForSequenceClassification")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-TransfoXLForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3894c76117dc4ca2f013cfe35221bfdfa429570dcba101381b815de15c3eb3c4
- Size of remote file:
- 4.59 MB
- SHA256:
- 9a5d59c4007d9dca3d8861b78c147ac036287351452b184a725bc8a689ae3f94
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