Update README.md

README.md

@@ -10,18 +10,12 @@ This LoRA trained for 3 epochs and has been converted to int4 (4bit) via GPTQ me
 
 Use the one of the two **safetensors** versions, the **pt** version is an old quantization that is no longer supported and will be removed in the future. Make sure you only have **ONE** checkpoint from the two in your model directory! See the repo below for more info.
 
-https://github.com/qwopqwop200/GPTQ-for-LLaMa
-
 LoRA credit to https://huggingface.co/baseten/alpaca-30b
 
-# Important - Update 2023-04-03
-Recent GPTQ commits have introduced breaking changes to model loading and you should use commit `a6f363e3f93b9fb5c26064b5ac7ed58d22e3f773` in the `cuda` branch. 
-
-If you're not familiar with the Git process
-1. `git checkout a6f363e3f93b9fb5c26064b5ac7ed58d22e3f773`
-2. `git switch -c cuda-stable`
+# Important - Update 2023-04-05
+Recent GPTQ commits have introduced breaking changes to model loading and you should this fork for a stable experience https://github.com/oobabooga/GPTQ-for-LLaMa
 
-This creates and switches to a `cuda-stable` branch to continue using the quantized models.
+Curently only cuda is supported.
 
 # Update 2023-03-29
 There is also a non-groupsize quantized model that is 1GB smaller in size, which should allow running at max context tokens with 24GB VRAM. The evaluations are better