Update README.md

README.md

@@ -4,11 +4,18 @@ datasets:
 - ehartford/wizard_vicuna_70k_unfiltered
 ---
 
+# Overview
 Fine-tuned [OpenLLaMA-7B](https://huggingface.co/openlm-research/open_llama_7b) with an uncensored/unfiltered Wizard-Vicuna conversation dataset [ehartford/wizard_vicuna_70k_unfiltered](https://huggingface.co/datasets/ehartford/wizard_vicuna_70k_unfiltered).
 Used QLoRA for fine-tuning. Trained for one epoch on a 24GB GPU (NVIDIA A10G) instance, took ~18 hours to train.
 
+# Training code
 Code used to train the model is available [here](https://github.com/georgesung/llm_qlora).
 
+# Demo
+For a Gradio chat application using this model, clone [this HuggingFace Space](https://huggingface.co/spaces/georgesung/open_llama_7b_qlora_uncensored_chat/tree/main) and run it on top of a GPU instance.
+The basic T4 GPU instance will work.
+
+# Blog post
 Since this was my first time fine-tuning an LLM, I also wrote an accompanying blog post about how I performed the training :)
 
 https://georgesung.github.io/ai/qlora-ift/