Instructions to use hf-tiny-model-private/tiny-random-YosoForSequenceClassification 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-YosoForSequenceClassification 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-YosoForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-YosoForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-YosoForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 95e25757b8a68f1ebb7a5700a04f0dae76d584b760d3c58e6ee0df355ef72356
- Size of remote file:
- 372 kB
- SHA256:
- 8ff1559c4950ddffa98b8c675816208475479f3794e132283f8f52943014df8b
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