Instructions to use hf-tiny-model-private/tiny-random-BloomForTokenClassification 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-BloomForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-BloomForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-BloomForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-BloomForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08c7681a20b651b2439610d3a0fe1ab0de805b83be7d86dee36c3211b439e133
- Size of remote file:
- 393 kB
- SHA256:
- 1ae1099a35e4295d98ecc4bb9ea45a92e447c0b61a09e3f962a0641d985db184
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