Instructions to use hf-internal-testing/tiny-random-MBartForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MBartForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-MBartForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MBartForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-MBartForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a9e2f64829cfe5b1a9e651118a337a9997156fdb3473c9c4fc6495621fb080e
- Size of remote file:
- 16.1 MB
- SHA256:
- acb0fd5a98a8543139755d48ba66b211bfc26a5b7eff41d8bb34f92475913abe
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