Instructions to use hf-internal-testing/tiny-random-MvpModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MvpModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-MvpModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MvpModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-MvpModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81c1c1960f24789938e37d6316b5753c964cb385816d6925d57fe4aa1ec8d97b
- Size of remote file:
- 118 kB
- SHA256:
- fb74438251db2174130d2cee3b2f96085aafc1212e44d0e1ecf15053d3e2beb6
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