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README.md
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@@ -60,6 +60,7 @@ pip3 install git+https://github.com/huggingface/transformers
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## Repositories available
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* [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/Llama-2-70B-chat-GPTQ)
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* [Original unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/TheBloke/Llama-2-70B-chat-fp16)
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## Prompt template: Llama-2-Chat
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- In text-generation-webui, you can add `:branch` to the end of the download name, eg `TheBloke/Llama-2-70B-chat-GPTQ:gptq-4bit-32g-actorder_True`
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- With Git, you can clone a branch with:
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```
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git clone --branch gptq-4bit-32g-actorder_True https://huggingface.co/TheBloke/Llama-2-70B-chat-GPTQ
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```
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- In Python Transformers code, the branch is the `revision` parameter; see below.
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### Use ExLlama (4-bit models only) - recommended option if you have enough VRAM for 4-bit
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ExLlama has now been updated to support Llama 2 70B
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By default text-generation-webui installs a pre-compiled wheel for ExLlama. Until text-generation-webui updates to reflect the ExLlama changes - which hopefully won't be long - you must uninstall that and then update ExLlama in the `text-generation-webui/repositories` directory. ExLlama will then compile its kernel on model load.
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Note that this requires that your system is capable of compiling CUDA extensions, which may be an issue on Windows.
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Instructions for Linux One Click Installer:
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1. Change directory into the text-generation-webui main folder: `cd /path/to/text-generation-webui`
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2. Activate the conda env of text-generation-webui:
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```
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source "installer_files/conda/etc/profile.d/conda.sh"
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conda activate installer_files/env
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```
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3. Run: `pip3 uninstall exllama`
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4. Run: `cd repositories/exllama` followed by `git pull` to update exllama.
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6. Now launch text-generation-webui and follow the instructions below for downloading and running the model. ExLlama should build its kernel when the model first loads.
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### Downloading and running the model in text-generation-webui
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## How to use this GPTQ model from Python code
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First make sure you have [AutoGPTQ](https://github.com/PanQiWei/AutoGPTQ) installed:
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```
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```
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You also need the latest Transformers code from Github:
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```
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pip3 install
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```
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You must set `inject_fused_attention=False` as shown below.
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ExLlama is now compatible with Llama 2 70B models, as of [this commit](https://github.com/turboderp/exllama/commit/b3aea521859b83cfd889c4c00c05a323313b7fee).
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<!-- footer start -->
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## Discord
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**Special thanks to**: Luke from CarbonQuill, Aemon Algiz.
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**Patreon special mentions**:
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Thank you to all my generous patrons and donaters!
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## Repositories available
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* [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/Llama-2-70B-chat-GPTQ)
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* [2, 3, 4, 5, 6 and 8-bit GGML models for CPU+GPU inference.](https://huggingface.co/TheBloke/Llama-2-70B-chat-GGML)
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* [Original unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/TheBloke/Llama-2-70B-chat-fp16)
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## Prompt template: Llama-2-Chat
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- In text-generation-webui, you can add `:branch` to the end of the download name, eg `TheBloke/Llama-2-70B-chat-GPTQ:gptq-4bit-32g-actorder_True`
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- With Git, you can clone a branch with:
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```
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git clone --single-branch --branch gptq-4bit-32g-actorder_True https://huggingface.co/TheBloke/Llama-2-70B-chat-GPTQ
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```
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- In Python Transformers code, the branch is the `revision` parameter; see below.
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### Use ExLlama (4-bit models only) - recommended option if you have enough VRAM for 4-bit
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ExLlama has now been updated to support Llama 2 70B. Make sure you're using the latest version of ExLlama, and text-generation-webui if you're using that.
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### Downloading and running the model in text-generation-webui
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## How to use this GPTQ model from Python code
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First make sure you have [AutoGPTQ](https://github.com/PanQiWei/AutoGPTQ) installed, version 0.3.1 or 0.3.2 or later:
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```
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pip3 install auto-gptq
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```
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You also need the latest Transformers code from Github:
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```
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pip3 install "transformers>=4.31.0"
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```
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You must set `inject_fused_attention=False` as shown below.
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ExLlama is now compatible with Llama 2 70B models, as of [this commit](https://github.com/turboderp/exllama/commit/b3aea521859b83cfd889c4c00c05a323313b7fee).
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Please see the Provided Files table above for per-file compatibility.
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<!-- footer start -->
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## Discord
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**Special thanks to**: Luke from CarbonQuill, Aemon Algiz.
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**Patreon special mentions**: Willem Michiel, Ajan Kanaga, Cory Kujawski, Alps Aficionado, Nikolai Manek, Jonathan Leane, Stanislav Ovsiannikov, Michael Levine, Luke Pendergrass, Sid, K, Gabriel Tamborski, Clay Pascal, Kalila, William Sang, Will Dee, Pieter, Nathan LeClaire, ya boyyy, David Flickinger, vamX, Derek Yates, Fen Risland, Jeffrey Morgan, webtim, Daniel P. Andersen, Chadd, Edmond Seymore, Pyrater, Olusegun Samson, Lone Striker, biorpg, alfie_i, Mano Prime, Chris Smitley, Dave, zynix, Trenton Dambrowitz, Johann-Peter Hartmann, Magnesian, Spencer Kim, John Detwiler, Iucharbius, Gabriel Puliatti, LangChain4j, Luke @flexchar, Vadim, Rishabh Srivastava, Preetika Verma, Ai Maven, Femi Adebogun, WelcomeToTheClub, Leonard Tan, Imad Khwaja, Steven Wood, Stefan Sabev, Sebastain Graf, usrbinkat, Dan Guido, Sam, Eugene Pentland, Mandus, transmissions 11, Slarti, Karl Bernard, Spiking Neurons AB, Artur Olbinski, Joseph William Delisle, ReadyPlayerEmma, Olakabola, Asp the Wyvern, Space Cruiser, Matthew Berman, Randy H, subjectnull, danny, John Villwock, Illia Dulskyi, Rainer Wilmers, theTransient, Pierre Kircher, Alexandros Triantafyllidis, Viktor Bowallius, terasurfer, Deep Realms, SuperWojo, senxiiz, Oscar Rangel, Alex, Stephen Murray, Talal Aujan, Raven Klaugh, Sean Connelly, Raymond Fosdick, Fred von Graf, chris gileta, Junyu Yang, Elle
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Thank you to all my generous patrons and donaters!
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