---
tags:
- roberta
- masked-language-modeling
- antibody
- humanization
- vh
- heavy chain
- OAS
- protein
- biology
license: mit
base_model:
- FacebookAI/roberta-base
pipeline_tag: fill-mask
---

# RoBERTa Base HumAb VH Model

This is a RoBERTa model trained from scratch for antibody humanization of Variable Heavy (VH) chain sequences using Masked Language Modeling (MLM).

## Model Description

This model was trained on approximately 141 million human antibody variable heavy chain (VH) sequences for humanization tasks. It achieves an accuracy of 91.46% and can be applied to antibody sequence analysis, humanization, and the study of VH chain patterns.

## Usage

```python
from transformers import RobertaTokenizer, RobertaForMaskedLM

# Load tokenizer and model from Hugging Face
tokenizer = RobertaTokenizer.from_pretrained("hemantn/roberta-base-humAb-vh")
model = RobertaForMaskedLM.from_pretrained("hemantn/roberta-base-humAb-vh")
```

## Using AnthroAb Python Package

For easier antibody humanization, you can use the [AnthroAb](https://github.com/nagarh/AnthroAb) Python package which provides a high-level interface for antibody humanization tasks. This package is available on PyPI and includes both VH and VL chain models.

### Installation

```bash
conda create -n anthroab python=3.10
conda activate anthroab
pip install anthroab
```

### Quick Usage

```python
import anthroab

# Humanize a heavy chain sequence (VH)
vh_sequence= "**QLV*SGVEVKKPGASVKVSCKASGYTFTNYYMYWVRQAPGQGLEWMGGINPSNGGTNFNEKFKNRVTLTTDSSTTTAYMELKSLQFDDTAVYYCARRDYRFDMGFDYWGQGTTVTVSS"
humanized_vh = anthroab.predict_masked(vh_sequence, 'H')
print(f"Humanized VH: {humanized_vh}")

# Humanize a light chain sequence (VL)
vl_sequence = "DIQMTQSPSSLSASV*DRVTITCRASQSISSYLNWYQQKPGKAPKLLIYSASTLASGVPSRFSGSGSGTDF*LTISSLQPEDFATYYCQQSYSTPRTFGQGTKVEIK"
humanized_vl = anthroab.predict_masked(vl_sequence, 'L')
print(f"Humanized VL: {humanized_vl}")
```

### Features

- **Easy Installation**: Install directly from PyPI with `pip install anthroab`
- **High-Level API**: Simple functions for antibody humanization
- **Dual Chain Support**: Separate models for VH and VL chains
- **Sequence Infilling**: Fill masked positions with human-like residues
- **Mutation Suggestions**: Get humanizing mutations for frameworks and CDRs
- **Embedding Generation**: Create vector representations of antibody sequences

The AnthroAb package uses this RoBERTa model (`hemantn/roberta-base-humAb-vh`) for VH chain humanization along with a companion VL model for light chain processing.

## Model Details

### Architecture
- **Model**: RoBERTa (trained from scratch)
- **Architecture**: RobertaForMaskedLM
- **Model Type**: Masked Language Model for antibody sequences

### Specifications
- **Hidden Size**: 768
- **Number of Layers**: 12
- **Number of Attention Heads**: 12
- **Intermediate Size**: 3072
- **Max Position Embeddings**: 192
- **Vocabulary Size**: 25 tokens
- **Model Size**: ~164 MB