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:
- e3f7f996f92230009e7448951bb8c18eedf6a14a450339bc93fe5464ff182c03
- Size of remote file:
- 938 kB
- SHA256:
- 96d3ea78f0752413384d561afe10dfaf1418ac736e6bb443be97afe8d3988387
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