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:
- df104dee5d6d9ae9f060e7952479b67a00be2621452ed11592b660fa9629d456
- Size of remote file:
- 172 kB
- SHA256:
- 212e222885f037f5f4dff214528de5f77e102110aea0c9d9619d369eac0ad0be
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