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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c25cb893e12ec2d82a51cb3640048cf7753225ba8429fcc598c801bfbf7b3bd3
- Size of remote file:
- 407 kB
- SHA256:
- 5ccc5ee48c7654cb4b2ac1dd6f43c29d624156714cc9b29815ef504368749718
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