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:
- ae1e8ec6d2a325d16da38d9d3da1e43e0eb2abd4373d4903d485615f9d782439
- Size of remote file:
- 474 kB
- SHA256:
- e25d88514bffdd156f5cbd5c9cf1121a161f31ddeb5554fcdcfbfb75bcdcc732
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