Instructions to use hf-internal-testing/tiny-random-PLBartModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PLBartModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-PLBartModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-PLBartModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-PLBartModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a2dd1b4480012be5be8f671c77c5af7a282972c83fd4fb6f89c8b65adcc5bf71
- Size of remote file:
- 3.25 MB
- SHA256:
- b4ff6a004a75ceb877c857fd52009798746ba79ba4e6f4dea4dca3ede94cee7e
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