Instructions to use hf-tiny-model-private/tiny-random-TransfoXLForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-TransfoXLForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-TransfoXLForSequenceClassification")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-TransfoXLForSequenceClassification", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 134a873adbf3db2065d6d457daece054e364d4b8b88f87b73747bab0c06440a6
- Size of remote file:
- 4.59 MB
- SHA256:
- 164cf116197884e4b78936e51fe54ad1e9c14dffd5f12bcc5ec49f70508168e5
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