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---
library_name: transformers, peft
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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.
Given a statement [ "During", "treatment", "with", "Hm", ",", "K562", "cells", "constitutively", "expressed", "c-myb", "mRNA", ",", "and", "50", "%", "of", "them", "began", "to", "synthesize", "hemoglobin", "(", "Hb", ")", "." ]
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 ]
And the label id categories are
{
"O": 0,
"B-DNA": 1,
"I-DNA": 2,
"B-protein": 3,
"I-protein": 4,
"B-cell_type": 5,
"I-cell_type": 6,
"B-cell_line": 7,
"I-cell_line": 8,
"B-RNA": 9,
"I-RNA": 10
}
More details can be found [here](https://huggingface.co/datasets/tner/bionlp2004?row=18)
- **Developed by:** PEFT Example
- **Model type:** Token Classification using LLM
- **Finetuned from:** model roberta-large
### Model Sources [optional]
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- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
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