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:
- f8f7483e93c7d3627c95a9cf28f71e1908186f4099e55c405822702d3cd66c45
- Size of remote file:
- 2.8 MB
- SHA256:
- c4699963745a11faa9eec251c186d9733111c7144ec3deba684a0cb3f0b4a1e1
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