Instructions to use hf-internal-testing/tiny-random-PhiForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PhiForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-PhiForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-PhiForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-PhiForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1a3e389cf078d2ed2cd97a5242623e49164ed77bffaa0f4fcad04ab6c503582
- Size of remote file:
- 189 kB
- SHA256:
- 64c96e38f2d5c8995413d1c6f0e5c9c2623f82d624f4a4ac95fd28949c746497
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