Instructions to use hf-internal-testing/tiny-random-CanineForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-CanineForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-CanineForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-CanineForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-CanineForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c2c5d38b29ff836bab8dc0cdca8b6d590d97ca63b8dd4650cb0c5b6330f9715d
- Size of remote file:
- 4.49 MB
- SHA256:
- e2fa77ff2787e45e70989d12d66c94b4acf4fbb1cd99b3fa6916796025546311
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