Instructions to use hf-internal-testing/tiny-random-BartForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BartForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-BartForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BartForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-BartForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cbf45476f32d46dba5cc26e3961f01566a32e74f61799ca88302a34a432e8f73
- Size of remote file:
- 120 kB
- SHA256:
- f57ee0ed8c8e7b7c6fad929fc9b398773573ca2e36bb26562540b97e533e9f2c
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