114 lines
3.8 KiB
Nix
114 lines
3.8 KiB
Nix
{ pkgs, lib, ... }:
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let
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models = [
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{
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name = "Qwen2.5-7B-Instruct-Q6_K_L.gguf";
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context_length = "131072";
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gen_length = "8192";
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source = pkgs.fetchurl {
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url = "https://huggingface.co/bartowski/Qwen2.5-7B-Instruct-GGUF/resolve/main/Qwen2.5-7B-Instruct-Q6_K_L.gguf?download=true";
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sha256 = "thEXN06T/UVGfzdB83jlgpG7kuTzZtz1ZUAdupAnErM=";
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};
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}
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{
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name = "Qwen2.5-14B-Instruct-Q4_K_S.gguf";
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context_length = "131072";
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gen_length = "8192";
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source = pkgs.fetchurl {
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url = "https://huggingface.co/bartowski/Qwen2.5-14B-Instruct-GGUF/resolve/main/Qwen2.5-14B-Instruct-Q4_K_S.gguf?download=true";
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sha256 = "E1CmWUhMMbTXEjIRczzA3rSrVuR8qOL8BLagw7LiyZk=";
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};
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}
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];
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#stolen from: https://stackoverflow.com/a/42398526
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optimizeWithFlags =
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pkg: flags:
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pkgs.lib.overrideDerivation pkg (
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old:
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let
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newflags = pkgs.lib.foldl' (acc: x: "${acc} ${x}") "" flags;
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oldflags = if (pkgs.lib.hasAttr "NIX_CFLAGS_COMPILE" old) then "${old.NIX_CFLAGS_COMPILE}" else "";
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in
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{
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NIX_CFLAGS_COMPILE = "${oldflags} ${newflags}";
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stdenv = pkgs.clangStdenv;
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}
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);
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model_files = builtins.listToAttrs (
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map (f: {
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name = ".local/share/nomic.ai/GPT4All/${f.name}";
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value = {
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source = f.source;
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};
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}) models
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);
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in
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{
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home.packages = with pkgs; [
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(optimizeWithFlags
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(gpt4all.overrideAttrs {
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src = fetchFromGitHub {
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fetchSubmodules = true;
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owner = "nomic-ai";
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repo = "gpt4all";
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rev = "HEAD";
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sha256 = "lGvxTOBg7/UgrCqeAFNFFXD9VjpUk3IVCktdUYuF6Eo=";
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};
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patches = [
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./gpt4all-HEAD-embeddings-model.patch
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./gpt4all-HEAD-disable-settings-err.patch
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];
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})
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# compile flags
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[
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"-Ofast"
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"-march=alderlake"
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"-mtune=alderlake"
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"-fno-protect-parens"
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"-fno-finite-math-only" # https://github.com/ggerganov/llama.cpp/pull/7154#issuecomment-2143844461
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]
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)
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];
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home.file = lib.recursiveUpdate {
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".config/nomic.ai/GPT4All.ini".text =
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let
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system_prompt = "You are an expert AI assistant that explains your reasoning step by step. For each step, provide a title that describes what you're doing in that step, along with the content. Decide if you need another step or if you're ready to give the final answer. USE AS MANY REASONING STEPS AS POSSIBLE. AT LEAST 3. BE AWARE OF YOUR LIMITATIONS AS AN LLM AND WHAT YOU CAN AND CANNOT DO. EXPLORE ALTERNATE ANSWERS AND CONSIDER THAT YOUR ANSWER MAY BE WRONG. IDENTIFY POSSIBLE ERRORS IN YOUR REASONING AND WHERE SUCH ERRORS MAY BE. FULLY TEST ALL OTHER POSSIBILITIES. YOU CAN BE WRONG. WHEN YOU SAY YOU ARE RE-EXAMINING, ACTUALLY RE-EXAMINE, AND USE ANOTHER APPROACH TO DO SO. DO NOT JUST SAY YOU ARE RE-EXAMINING. SHOW ALL YOUR WORK. USE AT LEAST 3 METHODS TO DERIVE THE ANSWER. USE BEST PRACTICES. WORK FROM FIRST PRINCIPLES TO CREATE YOUR ANSWER.";
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in
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''
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[General]
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chatTheme=Dark
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height=940
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suggestionMode=Off
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threadCount=8
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uniqueId=7096f2d2-448d-4272-a132-d37e77f8a781
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userDefaultModel=${(builtins.elemAt models 0).name}
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width=1472
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x=0
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y=0
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[download]
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lastVersionStarted=3.3.0-dev0
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[network]
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isActive=true
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usageStatsActive=true
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''
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+ (lib.concatStrings (
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map (model: ''
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[model-${model.name}]
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contextLength=${model.context_length}
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filename=${model.name}
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maxLength=${model.gen_length}
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promptBatchSize=256
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promptTemplate=<|im_start|>user\n%1<|im_end|>\n<|im_start|>assistant\n
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systemPrompt="<|im_start|>system\n${system_prompt}<|im_end|>
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\n"
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'') models
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));
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} model_files;
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}
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