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Initial commit : RoBERta-base HumAb VL model

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README.md ADDED
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+ ---
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+ tags:
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+ - roberta
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+ - masked-language-modeling
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+ - antibody
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+ - humanization
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+ - vl
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+ - light chain
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+ - OAS
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+ - protein
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+ - biology
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+ license: mit
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+ base_model:
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+ - FacebookAI/roberta-base
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+ pipeline_tag: fill-mask
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+ ---
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+
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+ # RoBERTa Base HumAb VL Model
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+
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+ This is a RoBERTa model trained from scratch for antibody humanization of Variable Light (VL) chain sequences using Masked Language Modeling (MLM).
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+
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+ ## Model Description
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+
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+ This model is trained on antibody light chain sequences (variable region) for humanization tasks. It can be used for antibody sequence analysis, humanization, and understanding of VL chain patterns.
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+
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+ ## Usage
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+
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+ ```python
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+ from transformers import RobertaTokenizer, RobertaForMaskedLM
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+
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+ # Load tokenizer and model from Hugging Face
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+ tokenizer = RobertaTokenizer.from_pretrained("hemantn/roberta-base-humAb-vl")
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+ model = RobertaForMaskedLM.from_pretrained("hemantn/roberta-base-humAb-vl")
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+ ```
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+
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+ ## Model Details
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+
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+ ### Architecture
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+ - **Model**: RoBERTa (trained from scratch)
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+ - **Architecture**: RobertaForMaskedLM
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+ - **Model Type**: Masked Language Model for antibody sequences
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+
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+ ### Specifications
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+ - **Hidden Size**: 768
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+ - **Number of Layers**: 12
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+ - **Number of Attention Heads**: 12
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+ - **Intermediate Size**: 3072
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+ - **Max Position Embeddings**: 145
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+ - **Vocabulary Size**: 25 tokens
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+ - **Model Size**: ~164 MB
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