Instructions to use hf-tiny-model-private/tiny-random-CanineModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-CanineModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-CanineModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-CanineModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-CanineModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 354fb55ae8146466293bdeddcbbdb4f2e6fb05703ef4c0886ffed5a20424c186
- Size of remote file:
- 4.49 MB
- SHA256:
- e8ff88c52d34cf231bf421517c9652484307320972c1641413918d3bf9daacb1
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