Instructions to use hf-internal-testing/tiny-random-BloomForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BloomForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-BloomForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BloomForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-BloomForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f0736981f355073f80f25f1b0fc7634a2a26743484458af5cd32a561609eec0
- Size of remote file:
- 407 kB
- SHA256:
- 9077bcb7e1fa1f6cc0213a83cd55c8f3ce29d60208e4e19ea701e0a6735d328b
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