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:
- ce45a66c926fd1ca9044d1ba5e44c7e54a036175530bd7943fb226a5ff385dcf
- Size of remote file:
- 211 kB
- SHA256:
- d19c9fde4b9a98a17b3a0358465e1bc47b93e8fe75b448f0c7673ee617e5ec7e
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