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:
- 17eb2f55169c5389a0704643c3a991c7fa1f49c560bc9f1b5642226cc05366db
- Size of remote file:
- 4.58 MB
- SHA256:
- 86b3605ced6605530ef8db91d596f7d8408ee41e13487186714e6a67e8aba7f0
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