Instructions to use hf-tiny-model-private/tiny-random-BloomForSequenceClassification 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-BloomForSequenceClassification 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-BloomForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-BloomForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-BloomForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c2e5f654aeff9e019cf94234b6eda4a688512901c1e1d65c521c154baab4e4ca
- Size of remote file:
- 393 kB
- SHA256:
- b21feb47982d3e0b1c37fbbfdbdc7b9bbf3e3a9ba093e14afa8c9390f1703221
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