Welcome to our NLP Model Fine-tuning Repository! This collection focuses on fine-tuning various Transformer-based models for specific Natural Language Processing (NLP) tasks.
- Albert_(updated).ipynb: Fine-tuning using Albert model.
- BLOOM.ipynb: Implementation of BLOOM for NLP tasks.
- DeBERTa(updated).ipynb: DeBERTa model fine-tuning notebook.
- Finetune_Flan_T5_(updated).ipynb: Fine-tuning Flan T5 model for specific tasks.
- RoBERTa(updated).ipynb: RoBERTa model fine-tuning notebook.
- finetune_ELECTRA(updated).ipynb: Fine-tuning the ELECTRA model.
Each notebook contains step-by-step instructions to fine-tune these models for various NLP tasks. Simply follow the provided guidelines to adapt the models to your specific needs.
- Clone this repository.
- Install the required dependencies as outlined within each notebook.
Follow the instructions detailed in the notebooks to fine-tune the Transformer models for your particular tasks.