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:
- 484c0c24a3eae1f36a32d89b1ddc80ac49432f636ea2bf12ebb7c1db21957886
- Size of remote file:
- 189 kB
- SHA256:
- 5399aa765ea39806f46a81ba1bd80ebbf3088a26cf6d4e992c1f94a829d396ab
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