Instructions to use hf-tiny-model-private/tiny-random-BartForSequenceClassification 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-BartForSequenceClassification 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-BartForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-BartForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-BartForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90ec02df22514b333370c50c1aea067f066a756787738417603d6fc5a8ad3351
- Size of remote file:
- 120 kB
- SHA256:
- 473b9b2eece3f56b543d464feb78c9dd94b1af9b61ecfbc2d32b94851633c9eb
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