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:
- 99ca21b60fb2404746e2f9c2b7d4107c80650de8c4a7e7580ead7f1d903cea89
- Size of remote file:
- 361 kB
- SHA256:
- fe2a45bdbcf803f4b39766a46aeff38f74a32f9ad5a0a8b018f6281bdce3ef28
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