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:
- 2e1aeff54c0098a6d260b5b1f3cfe83b6960cca38ae9a6e8401d77c27f0f64fd
- Size of remote file:
- 195 kB
- SHA256:
- 414fdabf9c33d82357532e1395d50d113f181fe5c8c2fcabc23c90a912c835e9
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