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:
- 3312fc767c568cde9ae882d0adc01a31469b9b3d3c782201553883565c9df33d
- Size of remote file:
- 140 kB
- SHA256:
- 16e80d3511a5b91b987b7f2dbea26e0db7d051edbacbd4f1592d5b76e7a03a50
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