Instructions to use hf-internal-testing/tiny-random-BertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-BertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-BertForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f07a3b1b917c089d067881da4398ee77f5ea9c48b4dc3f70c239b8876ddb25f9
- Size of remote file:
- 380 kB
- SHA256:
- 12bf8d2be229a9d2d305039619635dfa6036a7b84b70f9bbb6d33d2cc4745139
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