Instructions to use hf-tiny-model-private/tiny-random-MBartForSequenceClassification 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-MBartForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-MBartForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MBartForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-MBartForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c92610d48a72b66bffd5d7fd6dc8f25a1d92ce30416e91f8169a1ddb2dcf55e2
- Size of remote file:
- 16.1 MB
- SHA256:
- f210ffd980d790cf28299d615fee3fb989bd3722a1c1116a8c8eb7d769579f24
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