Update README.md

README.md

@@ -1,3 +1,41 @@
 ---
+base_model:
+- InferenceIllusionist/Excalibur-7b
+library_name: transformers
+tags:
+- finetune
+- dpo
+- chatml
+- gguf
 license: apache-2.0
+datasets:
+- Intel/orca_dpo_pairs
 ---
+
+
+# Excalibur-7b-DPO-GGUF
+
+<img src="https://i.imgur.com/pbPbqq0.jpeg" width="550"/>
+
+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*
+
+<b>FP16 available [here](https://huggingface.co/InferenceIllusionist/Excalibur-7b-DPO)</b>
+
+## Notes & Methodology
+* [Excalibur-7b](https://huggingface.co/InferenceIllusionist/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
+<img src="https://i.imgur.com/7aRWtzU.jpeg" width="425"/>
+
+<b>Requires additional [mistral-7b-mmproj-v1.5-Q4_1.gguf](https://huggingface.co/koboldcpp/mmproj/tree/main) file for vision functionality</b>
+
+Select 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:
+<img src="https://i.imgur.com/x8vqH29.png" width="425"/>
+
+## Prompt Format
+* For best results please use ChatML for the prompt format. Alpaca may also work.