metadata
base_model:
- InferenceIllusionist/Excalibur-7b
library_name: transformers
tags:
- finetune
license: apache-2.0
datasets:
- Intel/orca_dpo_pairs
Excalibur-7b-DPO
An initial foray into the world of fine-tuning. The goal of this release was to amplify the quality of the original model's responses, in particular for vision use cases*
Notes & Methodology
- Excalibur-7b fine-tuned with Direct Preference Optimization (DPO) using Intel/orca_dpo_pairs
- This is a quick experiment to determine the impact of DPO finetuning on the original base model
- Ran for a little over an hour on a single A100
- Internal benchmarks showed improvement over base model, awaiting final results
- Precision: bfloat16
Sample Question - Vision
Requires additional mistral-7b-mmproj-v1.5-Q4_1.gguf file for vision functionality
Select up the gguf file of your choice in Kobold as usual, then make sure to choose the mmproj file above in the LLaVA mmproj field of the model submenu: