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:
- 84d747c4f62bf8cdd92050ab856139dafb22d908c9015cc02cb5cf0733435885
- Size of remote file:
- 189 kB
- SHA256:
- c5f31106c411c3c12fc5ddfdf35efb77e302b75a62106b2c4e62d94d6ea56a19
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