Instructions to use slightlycodic/TC-ABB-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use slightlycodic/TC-ABB-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="slightlycodic/TC-ABB-BERT")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("slightlycodic/TC-ABB-BERT") model = AutoModelForTokenClassification.from_pretrained("slightlycodic/TC-ABB-BERT") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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model-index:
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results: []
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- Transformers 4.51.1
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- Pytorch 2.6.0+cu124
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- Datasets 3.5.0
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- Tokenizers 0.21.1
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model-index:
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- name: bert-base-uncased
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results: []
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datasets:
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- surrey-nlp/PLOD-CW-25
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- Transformers 4.51.1
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- Pytorch 2.6.0+cu124
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- Datasets 3.5.0
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- Tokenizers 0.21.1
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