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:
- 1016126ab9f4bc6514f20e8af13bf2e15fd2500e16e4f05975dbd397d8e972e7
- Size of remote file:
- 189 kB
- SHA256:
- 7f12a3ae8e25e62f61a5b8ab0d80718e26971fcf8ec54763973391c9d1a1faaa
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