Instructions to use optimum-intel-internal-testing/ov-tiny-random-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use optimum-intel-internal-testing/ov-tiny-random-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="optimum-intel-internal-testing/ov-tiny-random-distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("optimum-intel-internal-testing/ov-tiny-random-distilbert") model = AutoModelForSequenceClassification.from_pretrained("optimum-intel-internal-testing/ov-tiny-random-distilbert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca1f2a9fd179b649e1c9f12f3f181ef9c3daf1defb450fef3ef837a9994c845c
- Size of remote file:
- 347 kB
- SHA256:
- fe214f56bc98fcfa0f4fbbd01b73238d54171d0ee6fd10c2ef961d94ea199784
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