Instructions to use hf-tiny-model-private/tiny-random-BartModel 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-BartModel 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-BartModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-BartModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-BartModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 50091c517a1b703fa0684a3c37d2acc5e0f25536203ee05240da3c7b6ebd6a6e
- Size of remote file:
- 137 kB
- SHA256:
- 0204415ebcf27377e0a01f3ec86c52cdbd13158ad4c336ff47e77c103c8463d0
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