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:
- 52ca72650c994e07adaa163ae63fe83c8e97be14d765903f5776f63658af3e80
- Size of remote file:
- 957 kB
- SHA256:
- ec2dc1e7672d9d0fc3b3a3ec0da3da7a3e2fe6b8da5ca26ce8e0fe6b27e91ea5
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