Instructions to use huggingface-hub-ci/test-model-on-the-fly-f9a92262-285c-456a-a322-6164fd1ea529 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huggingface-hub-ci/test-model-on-the-fly-f9a92262-285c-456a-a322-6164fd1ea529 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="huggingface-hub-ci/test-model-on-the-fly-f9a92262-285c-456a-a322-6164fd1ea529")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("huggingface-hub-ci/test-model-on-the-fly-f9a92262-285c-456a-a322-6164fd1ea529") model = AutoModel.from_pretrained("huggingface-hub-ci/test-model-on-the-fly-f9a92262-285c-456a-a322-6164fd1ea529") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 05329bfaab62bf1092788e7a9830f818c4a791fd599fa81aed48e50b9acc7729
- Size of remote file:
- 247 kB
- SHA256:
- a3630b502976a3cb952d1ed54c1248a152ee265ea131a74a07c68790a7740d45
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