Instructions to use hf-tiny-model-private/tiny-random-CanineForSequenceClassification 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-CanineForSequenceClassification 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-CanineForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-CanineForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-CanineForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ca53b1148d74875f0779f4c9266812d3d7be27d51855012d93f15a68f4badf0
- Size of remote file:
- 4.46 MB
- SHA256:
- 7d68dd985692e70fce9268b9193c7cbf29a56b638ee28e9b071a685a8e813333
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