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:
- 8eee26b0c14f24e34a85ca7d4be00af06301cf20f091610143d7c9a128a864f3
- Size of remote file:
- 986 kB
- SHA256:
- f72f5d040a176945623a255484d24066f8c0da89a294359154e226efbe494b80
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