Instructions to use tavtav/Magnum-v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tavtav/Magnum-v5 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("C:\\Users\\Tav\\Downloads\\Hamanasu-KTO-V2") model = PeftModel.from_pretrained(base_model, "tavtav/Magnum-v5") - Notebooks
- Google Colab
- Kaggle
| base_model: [] | |
| library_name: peft | |
| tags: | |
| - mergekit | |
| - peft | |
| # Hamanasu-Lora-Extracted | |
| This is a LoRA extracted from a language model. It was extracted using [mergekit](https://github.com/arcee-ai/mergekit). | |
| ## LoRA Details | |
| This LoRA adapter was extracted from C:\Users\Tav\Downloads\Hamanasu-Magnum-4B-Ckpts and uses C:\Users\Tav\Downloads\Hamanasu-KTO-V2 as a base. | |
| ### Parameters | |
| The following command was used to extract this LoRA adapter: | |
| ```sh | |
| E:\Users\Tav\miniconda3\Scripts\mergekit-extract-lora --model C:\Users\Tav\Downloads\Hamanasu-Magnum-4B-Ckpts --base-model C:\Users\Tav\Downloads\Hamanasu-KTO-V2 --out-path C:\Users\Tav\Downloads\Hamanasu-Lora-Extracted --max-rank=128 | |
| ``` | |