Instructions to use hf-tiny-model-private/tiny-random-MPNetForTokenClassification 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-MPNetForTokenClassification 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-MPNetForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MPNetForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-MPNetForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ef3948b78bc2254d8154d09a15bf302da42a4ca0a3f32b1d44cbc97843f633a
- Size of remote file:
- 1.07 MB
- SHA256:
- c94bcaba506dc77827e3a41d8d276bcc461dced4db20f5fd51ac75b7e557d519
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