Instructions to use hf-tiny-model-private/tiny-random-IBertForTokenClassification 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-IBertForTokenClassification 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-IBertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-IBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-IBertForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f520ccb21eafc4398400efc61d292ea85f175c396732bb827272c98f513db497
- Size of remote file:
- 813 kB
- SHA256:
- 56729e239fc7b38f7f39421b3ea280203f8bf192bcd3413396707f93e6ed020d
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