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--- |
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library_name: transformers, peft |
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tags: [] |
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--- |
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# Model Card for Model ID |
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<!-- Provide a quick summary of what the model is/does. --> |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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This is the an implementation of the Token Classification as mentioned [here](https://huggingface.co/docs/peft/task_guides/token-classification-lora). A PEFT model has been fine tuned to a token classification task for Bio Entity recognition from base model of roberta-large. Objective is to identify BIO Named Entity Recognition. |
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Given a statement [ "During", "treatment", "with", "Hm", ",", "K562", "cells", "constitutively", "expressed", "c-myb", "mRNA", ",", "and", "50", "%", "of", "them", "began", "to", "synthesize", "hemoglobin", "(", "Hb", ")", "." ] |
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it would generate the tags [ 0, 0, 0, 3, 0, 7, 8, 0, 0, 9, 10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0 ] |
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And the label id categories are |
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{ |
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"O": 0, |
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"B-DNA": 1, |
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"I-DNA": 2, |
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"B-protein": 3, |
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"I-protein": 4, |
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"B-cell_type": 5, |
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"I-cell_type": 6, |
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"B-cell_line": 7, |
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"I-cell_line": 8, |
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"B-RNA": 9, |
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"I-RNA": 10 |
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} |
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More details can be found [here](https://huggingface.co/datasets/tner/bionlp2004?row=18) |
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- **Developed by:** PEFT Example |
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- **Model type:** Token Classification using LLM |
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- **Finetuned from:** model roberta-large |
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### Model Sources [optional] |
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<!-- Provide the basic links for the model. --> |
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- **Repository:** [More Information Needed] |
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- **Paper [optional]:** [More Information Needed] |
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- **Demo [optional]:** [More Information Needed] |
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