Instructions to use hf-tiny-model-private/tiny-random-MvpModel 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-MvpModel 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-MvpModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MvpModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-MvpModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d7a9d8da81e3dd569a9957aeefcf1c1f26d9923face212379b087f3caaf08ea3
- Size of remote file:
- 118 kB
- SHA256:
- 7ee33cf58efaef7400757572fa297dee1a683faeeff34e8d33d52f424598562d
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