From 1c78ffb964c6bbe01af2cc35b45fab5671de2f84 Mon Sep 17 00:00:00 2001
From: LostRuins <39025047+LostRuins@users.noreply.github.com>
Date: Fri, 24 Mar 2023 22:45:54 +0800
Subject: [PATCH] Update README.md

---
 README.md | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/README.md b/README.md
index 83efc7eb7..292046f20 100644
--- a/README.md
+++ b/README.md
@@ -8,10 +8,10 @@ What does it mean? You get llama.cpp with a fancy UI, persistent stories, editin
 
 ## Usage
 - [Download the latest release here](https://github.com/LostRuins/llamacpp-for-kobold/releases/latest) or clone the repo.
-- Windows binaries are provided in the form of **llamacpp.dll** but if you feel worried go ahead and rebuild it yourself.
-- Weights are not included, you can use the llama.cpp quantize.exe to generate them from your official weight files (or download them from...places).
-- To run, execute the script providing the model as a parameter `llama_for_kobold.py [ggml_quant_model.bin] [port]`, and then connect with Kobold or Kobold Lite. 
-- By default, you can connect to http://localhost:5001 (you can also use https://lite.koboldai.net/?local=1&port=5001).
+- Windows binaries are provided in the form of **llamacpp-for-kobold.exe**, which is a pyinstaller wrapper for **llamacpp.dll** and **llama-for-kobold.py**. If you feel concerned, you may prefer to rebuild it yourself with the provided makefiles and scripts.
+- Weights are not included, you can use the `quantize.exe` to generate them from your official weight files (or download them from other places).
+- To run, execute **llamacpp-for-kobold.exe** or drag and drop your quantized ggml model.bin file onto the .exe, and then connect with Kobold or Kobold Lite. 
+- By default, you can connect to http://localhost:5001 
 
 ## Considerations
 - Don't want to use pybind11 due to dependencies on MSVCC