Instructions to use hf-tiny-model-private/tiny-random-PLBartModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-PLBartModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-PLBartModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-PLBartModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-PLBartModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed962c6659ffd3c7e85467cdf14dca146b2e3b08226195cedf60522f9e7ee39c
- Size of remote file:
- 3.27 MB
- SHA256:
- 5b0f7093f87c5b53a403e81377f5fd5505df6dd71a4dfc4da68f9e852348675c
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