Instructions to use qgallouedec/tiny-BartModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use qgallouedec/tiny-BartModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="qgallouedec/tiny-BartModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("qgallouedec/tiny-BartModel") model = AutoModel.from_pretrained("qgallouedec/tiny-BartModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b1662debf34d637f9505ab638c01a62bf72f5e8701c61e84ce4e97f702330338
- Size of remote file:
- 5.55 MB
- SHA256:
- 022b4ceabeb6427c5e9e2091b36154515c12e79950912a5ee90191a5b7346811
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