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:
- 0abcf57a6175f996d452608b04e1cfc4a3eaaf2da47c2f034335c9e6844f88a0
- Size of remote file:
- 189 kB
- SHA256:
- 8efa711d5a9ed2deacaa361982051a4acf882b44ac0d904f85a88b524d11d578
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