Instructions to use hf-tiny-model-private/tiny-random-MobileBertForTokenClassification 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-MobileBertForTokenClassification 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-MobileBertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MobileBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-MobileBertForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c948a3fb0b49b56b91d7a99720bd874b417624324d1c74bbd9bad85d1bab25d
- Size of remote file:
- 3.11 MB
- SHA256:
- ac26b8710583c26a9f8dcab86cd6f482243392d4527c532d562bab33224b11f6
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