Instructions to use huggingface-hub-ci/test-model-on-the-fly-f336e3fa-90db-43cd-9ea8-28a257507ba3 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-f336e3fa-90db-43cd-9ea8-28a257507ba3 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-f336e3fa-90db-43cd-9ea8-28a257507ba3")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("huggingface-hub-ci/test-model-on-the-fly-f336e3fa-90db-43cd-9ea8-28a257507ba3") model = AutoModel.from_pretrained("huggingface-hub-ci/test-model-on-the-fly-f336e3fa-90db-43cd-9ea8-28a257507ba3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a097134345129a6f21b76f9eee3ea318b62c8f1a59b1c69daa69b487e1899b3b
- Size of remote file:
- 247 kB
- SHA256:
- fea77acfbdcb406e8229ff0b71952d6a4abbe7f4ba7e02265c687663adc3dbef
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