Instructions to use hf-tiny-model-private/tiny-random-MegatronBertForTokenClassification 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-MegatronBertForTokenClassification 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-MegatronBertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MegatronBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-MegatronBertForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 488df449698acf387110e4163359355641f5813053bf542f0ef2617b34fb701c
- Size of remote file:
- 890 kB
- SHA256:
- 3e7885771ac1d311c067e538b0fa1161a5f04c771b1cfb49492249d840914900
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