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:
- bdacea5c63e49b7664fb6d38597647b9f870f31b1e496416dcece150d0503204
- Size of remote file:
- 224 kB
- SHA256:
- 693215174f35ddf43c42a815d14c3ea3113163358c6c4f0cd008cb3d74ec7ead
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