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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 10d3c68463b48595a8f3db513fb7524d8e4fb71aa80c25127a133b96aa0cea9e
- Size of remote file:
- 16.1 MB
- SHA256:
- f606abdb5288b1cd41c65e91637a01a0b9df27422c001fe2b4ba19ca09511a0b
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