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:
- bdb62fef1f0cc8a5e4164df2e6dd6fab574a3fbd41ae1e3a8fcfc1e4001d4402
- Size of remote file:
- 3.25 MB
- SHA256:
- fb7f2bd57fda58698643329aaee6727697b396a893f7d84600af5c262a04f61f
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