Update README.md

README.md

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 ---
+base_model:
+- InferenceIllusionist/Excalibur-7b
+library_name: transformers
+tags:
+- finetune
+- dpo
+- chatml
+- gguf
+- imat
 license: apache-2.0
+datasets:
+- Intel/orca_dpo_pairs
 ---
+
+
+# Excalibur-7b-DPO-iMat-GGUF
+
+<img src="https://i.imgur.com/pbPbqq0.jpeg" width="550"/>
+
+Quantized from fp32 with love. 
+
+iMatrix .dat file was calculated using groups_merged.txt.
+
+<b>FP16 available [here](https://huggingface.co/InferenceIllusionist/Excalibur-7b-DPO)</b>
+
+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](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 mmproj file. You have two options for vision functionality (available inside original repo or linked below):</b>
+ * [Quantized - Limited VRAM Option (197mb)](https://huggingface.co/InferenceIllusionist/Excalibur-7b-DPO-GGUF/resolve/main/mistral-7b-mmproj-v1.5-Q4_1.gguf?download=true)
+ * [Unquantized - Premium Option / Best Quality (596mb)](https://huggingface.co/InferenceIllusionist/Excalibur-7b-DPO-GGUF/resolve/main/mmproj-model-f16.gguf?download=true)
+
+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.
+
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_InferenceIllusionist__Excalibur-7b-DPO)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |73.84|
+|AI2 Reasoning Challenge (25-Shot)|70.90|
+|HellaSwag (10-Shot)              |87.93|
+|MMLU (5-Shot)                    |65.46|
+|TruthfulQA (0-shot)              |70.82|
+|Winogrande (5-shot)              |82.48|
+|GSM8k (5-shot)                   |65.43|