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:
- 82b25585de3f767933ddf4ef734af4fb9a2b41d7ebf88318688e9c5c3c140fca
- Size of remote file:
- 4.46 MB
- SHA256:
- d0392617a40b9c8dd21b8972557ea58ee2fbe2d8b21aa65a0958e412601a81bb
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