Update README.md

README.md

@@ -32,49 +32,25 @@ I haven't specifically tested VRAM requirements yet but will aim to do so at som
 
 If you want to try CPU inference instead, check out my GGML repo: [TheBloke/alpaca-lora-65B-GGML](https://huggingface.co/TheBloke/alpaca-lora-65B-GGML).
 
-## GIBBERISH OUTPUT IN `text-generation-webui`?
-
-Please read the Provided Files section below. You should use `alpaca-lora-65B-GPTQ-4bit-128g.no-act-order.safetensors` unless you are able to use the latest Triton branch of GPTQ-for-LLaMa.
-
 ## Provided files
 
-Three files are provided. **The second and third files will not work unless you use a recent version of the Triton branch of GPTQ-for-LLaMa**
-
-Specifically, the last two files use `--act-order` for maximum quantisation quality and will not work with oobabooga's fork of GPTQ-for-LLaMa. Therefore at this time it will also not work with the CUDA branch of GPTQ-for-LLaMa, or `text-generation-webui` one-click installers.
+Three files are provided, in separate branches.
 
-Unless you are able to use the latest Triton GPTQ-for-LLaMa code, please use `medalpaca-13B-GPTQ-4bit-128g.no-act-order.safetensors`
-
-* `alpaca-lora-65B-GPTQ-4bit-128g.no-act-order.safetensors`
-  * Works with all versions of GPTQ-for-LLaMa code, both Triton and CUDA branches
-  * Works with text-generation-webui one-click-installers
-  * Works on Windows
+* `alpaca-lora-65B-GPTQ-4bit-128g.no-act-order.safetensors` - branch main
   * Will require ~40GB of VRAM, meaning you'll need an A100 or 2 x 24GB cards.
-  * I haven't yet tested how much VRAM is required exactly so it's possible it won't run on an A100 40GB
   * Parameters: Groupsize = 128g. No act-order.
   * Command used to create the GPTQ:
     ```
     CUDA_VISIBLE_DEVICES=0 python3 llama.py alpaca-lora-65B-HF c4 --wbits 4 --true-sequential --groupsize 128 --save_safetensors alpaca-lora-65B-GPTQ-4bit-128g.no-act-order.safetensors
     ```
-* `alpaca-lora-65B-GPTQ-4bit-128g.safetensors`
-  * Only works with the latest Triton branch of GPTQ-for-LLaMa
-  * **Does not** work with text-generation-webui one-click-installers
-  * **Does not** work on Windows
-  * Will require 40+GB of VRAM, meaning you'll need an A100 or 2 x 24GB cards.
-  * I haven't yet tested how much VRAM is required exactly so it's possible it won't run on an A100 40GB
+* `alpaca-lora-65B-GPTQ-4bit-128g.safetensors` - branch gptq-4bit-128g-actorder_True
   * Parameters: Groupsize = 128g. act-order.
-  * Offers highest quality quantisation, but requires recent Triton GPTQ-for-LLaMa code and more VRAM
   * Command used to create the GPTQ:
     ```
     CUDA_VISIBLE_DEVICES=0 python3 llama.py alpaca-lora-65B-HF c4 --wbits 4 --true-sequential --act-order --groupsize 128 --save_safetensors alpaca-lora-65B-GPTQ-4bit-128g.safetensors
     ```
-* `alpaca-lora-65B-GPTQ-4bit-1024g.safetensors`
-  * Only works with the latest Triton branch of GPTQ-for-LLaMa
-  * **Does not** work with text-generation-webui one-click-installers
-  * **Does not** work on Windows
-  * Should require less VRAM than the 128g file, so hopefully it will run in an A100 40GB
-  * I haven't yet tested how much VRAM is required exactly
+* `alpaca-lora-65B-GPTQ-4bit-1024g.safetensors` - branch gptq-4bit-1024g-actorder_True
   * Parameters: Groupsize = 1024g. act-order.
-  * Offers the benefits of act-order, but at a higher groupsize to reduce VRAM requirements
   * Command used to create the GPTQ:
     ```
     CUDA_VISIBLE_DEVICES=0 python3 llama.py alpaca-lora-65B-HF c4 --wbits 4 --true-sequential --act-order --groupsize 1024 --save_safetensors alpaca-lora-65B-GPTQ-4bit-1024g.safetensors
@@ -82,32 +58,7 @@ Unless you are able to use the latest Triton GPTQ-for-LLaMa code, please use `me
 
 ## How to run in `text-generation-webui`
 
-File `alpaca-lora-65B-GPTQ-4bit-128g.no-act-order.safetensors` can be loaded the same as any other GPTQ file, without requiring any updates to [oobaboogas text-generation-webui](https://github.com/oobabooga/text-generation-webui).
-
-[Instructions on using GPTQ 4bit files in text-generation-webui are here](https://github.com/oobabooga/text-generation-webui/wiki/GPTQ-models-\(4-bit-mode\)).
-
-The other two `safetensors` model files were created using `--act-order` to give the maximum possible quantisation quality, but this means it requires that the latest Triton GPTQ-for-LLaMa is used inside the UI.
-
-If you want to use the act-order `safetensors` files and need to update the Triton branch of GPTQ-for-LLaMa, here are the commands I used to clone the Triton branch of GPTQ-for-LLaMa, clone text-generation-webui, and install GPTQ into the UI:
-```
-# Clone text-generation-webui, if you don't already have it
-git clone https://github.com/oobabooga/text-generation-webui
-# Make a repositories directory
-mkdir text-generation-webui/repositories
-cd text-generation-webui/repositories
-# Clone the latest GPTQ-for-LLaMa code inside text-generation-webui
-git clone https://github.com/qwopqwop200/GPTQ-for-LLaMa
-```
-
-Then install this model into `text-generation-webui/models` and launch the UI as follows:
-```
-cd text-generation-webui
-python server.py --model alpaca-lora-65B-GPTQ-4bit --wbits 4 --groupsize 128 --model_type Llama # add any other command line args you want
-```
-
-The above commands assume you have installed all dependencies for GPTQ-for-LLaMa and text-generation-webui. Please see their respective repositories for further information.
-
-If you can't update GPTQ-for-LLaMa to the latest Triton branch, or don't want to, you can use `alpaca-lora-65B-GPTQ-4bit-128g.no-act-order.safetensors` as mentioned above, which should work without any upgrades to text-generation-webui.
+Please see one of my more recent repos for instructions on loading GPTQ models in text-generation-webui.
 
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