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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9823b6f94defa41c9dd545791c07b8c2f2668ceee4c5a7482b0eae4e6ddf0965
- Size of remote file:
- 140 kB
- SHA256:
- 0dc700f870b65a4c5e1bf1b9804eed849ec830c80684afc05e25f25d364c557d
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