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:
- 6a1c7cdeba0e3488a70bea6f7df76770c4f73577832258dbb11a37216d52dda7
- Size of remote file:
- 872 kB
- SHA256:
- b960d527139ac4803b84bcd9593d8d019986220288d167c2924f733733b48bdc
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