Instructions to use hf-internal-testing/tiny-random-ReformerForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ReformerForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-ReformerForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ReformerForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-ReformerForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c07234d3f574d050186ae108211ebb2cdf475906535fc0f3f8006c2023d9369
- Size of remote file:
- 358 kB
- SHA256:
- e867cb087d26336788daece8e68fd787fda34b9bd8b1efd32930997b67c5be02
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