Instructions to use hf-tiny-model-private/tiny-random-BartModel 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-BartModel 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-BartModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-BartModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-BartModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc38cdfe201d91e2a08d9f287c604a482aa09c92ffbc4c63a4fec7419d2d4cb9
- Size of remote file:
- 118 kB
- SHA256:
- 62d5b45671d6b15a344c2e7980c7d74d05c703692a89b8db58afa0a96118c418
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