Fine-tuning and model merge techniques for large language models, low-rank (LORA) techniques to fine-tune LLMs efficiently with limited computational resources. Merge LLMs fine-tuned to different tasks without further training to get a resulting model with even better performance.
Jupyter Notebook
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63 commits
updated Dec 21, 2024
Fine-tuning and model merge techniques for large language models, low-rank (LORA) techniques to fine-tune LLMs efficiently with limited computational resources. Merge LLMs fine-tuned to different tasks without further training to get a resulting model with even better performance.
The "Project Notebook.ipynb" file contains all the code necessary to run the different methods implemented in this project
Fine-tuning and model merge techniques for large language models, low-rank (LORA) techniques to fine-tune LLMs efficiently with limited computational resources. Merge LLMs fine-tuned to different tasks without further training to get a resulting model with even better performance.
Jupyter Notebook
0
63 commits
updated Dec 21, 2024
Fine-tuning and model merge techniques for large language models, low-rank (LORA) techniques to fine-tune LLMs efficiently with limited computational resources. Merge LLMs fine-tuned to different tasks without further training to get a resulting model with even better performance.
The "Project Notebook.ipynb" file contains all the code necessary to run the different methods implemented in this project
