Instructions to use hf-internal-testing/tiny-random-BartModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BartModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-BartModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BartModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-BartModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c2da947915ba587dfa8c81dc0ac6ef78229bab1f60c74306840c197d207c5edc
- Size of remote file:
- 118 kB
- SHA256:
- 751ddf1b786adf0b6c99316cec86c77b4ad621142007cedf62260ba5f05d42e4
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