Instructions to use hf-internal-testing/tiny-random-MPNetForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MPNetForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-MPNetForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MPNetForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-MPNetForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ce426c48969a5684b4e83cc80f79e29c53bd642a88d9fc2acec82485f7212171
- Size of remote file:
- 1.07 MB
- SHA256:
- 508f63e59b6f15e544614ae979f0c7ca0ab7b84cc5d6941f1d1912fce97b859a
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