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", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13fd6a02b48ee81fc722f5a64c923c1cd47e5085fb3acc355b3e06ce395700dd
- Size of remote file:
- 5.38 MB
- SHA256:
- 546e48c575ff2cfb930135f876efde71e871eb50a4715186e3c4ad19428c3005
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