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:
- 86af8fd1d04d990ba420dc50b508c23fe0a59968192eb978e2f5226f7031e2c4
- Size of remote file:
- 140 kB
- SHA256:
- 2d7c74904466549255b6f4057186d87ecbab35325408c58294806c47bc6ae17e
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