Safetensors
GGUF
Turkish
llama
Llama-3
instruct
finetune
chatml
gpt4
synthetic data
distillation
function calling
json mode
axolotl
roleplaying
chat
Instructions to use tda45/TdAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use tda45/TdAI with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="tda45/TdAI", filename="llama.cpp/models/ggml-vocab-aquila.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tda45/TdAI with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf tda45/TdAI # Run inference directly in the terminal: llama cli -hf tda45/TdAI
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tda45/TdAI # Run inference directly in the terminal: llama cli -hf tda45/TdAI
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf tda45/TdAI # Run inference directly in the terminal: ./llama-cli -hf tda45/TdAI
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf tda45/TdAI # Run inference directly in the terminal: ./build/bin/llama-cli -hf tda45/TdAI
Use Docker
docker model run hf.co/tda45/TdAI
- LM Studio
- Jan
- Ollama
How to use tda45/TdAI with Ollama:
ollama run hf.co/tda45/TdAI
- Unsloth Studio
How to use tda45/TdAI with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for tda45/TdAI to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for tda45/TdAI to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tda45/TdAI to start chatting
- Atomic Chat new
- Docker Model Runner
How to use tda45/TdAI with Docker Model Runner:
docker model run hf.co/tda45/TdAI
- Lemonade
How to use tda45/TdAI with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tda45/TdAI
Run and chat with the model
lemonade run user.TdAI-{{QUANT_TAG}}List all available models
lemonade list
File size: 8,078 Bytes
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lib,
glibc,
config,
stdenv,
stdenvNoCC,
runCommand,
cmake,
ninja,
pkg-config,
git,
mpi,
blas,
cudaPackages,
autoAddDriverRunpath,
darwin,
rocmPackages,
vulkan-headers,
vulkan-loader,
openssl,
shaderc,
spirv-headers,
nodejs,
importNpmLock,
useBlas ?
builtins.all (x: !x) [
useCuda
useMetalKit
useRocm
useVulkan
]
&& blas.meta.available,
useCuda ? config.cudaSupport,
useMetalKit ? stdenv.isAarch64 && stdenv.isDarwin,
# Increases the runtime closure size by ~700M
useMpi ? false,
useRocm ? config.rocmSupport,
rocmGpuTargets ? builtins.concatStringsSep ";" rocmPackages.clr.gpuTargets,
useVulkan ? false,
useRpc ? false,
llamaVersion ? "0.0.0", # Arbitrary version, substituted by the flake
# It's necessary to consistently use backendStdenv when building with CUDA support,
# otherwise we get libstdc++ errors downstream.
effectiveStdenv ? if useCuda then cudaPackages.backendStdenv else stdenv,
enableStatic ? effectiveStdenv.hostPlatform.isStatic,
precompileMetalShaders ? false,
useWebUi ? true,
}:
let
inherit (lib)
cmakeBool
cmakeFeature
optionalAttrs
optionals
strings
;
stdenv = throw "Use effectiveStdenv instead";
suffices =
lib.optionals useBlas [ "BLAS" ]
++ lib.optionals useCuda [ "CUDA" ]
++ lib.optionals useMetalKit [ "MetalKit" ]
++ lib.optionals useMpi [ "MPI" ]
++ lib.optionals useRocm [ "ROCm" ]
++ lib.optionals useVulkan [ "Vulkan" ];
pnameSuffix =
strings.optionalString (suffices != [ ])
"-${strings.concatMapStringsSep "-" strings.toLower suffices}";
descriptionSuffix = strings.optionalString (
suffices != [ ]
) ", accelerated with ${strings.concatStringsSep ", " suffices}";
xcrunHost = runCommand "xcrunHost" { } ''
mkdir -p $out/bin
ln -s /usr/bin/xcrun $out/bin
'';
# apple_sdk is supposed to choose sane defaults, no need to handle isAarch64
# separately
darwinBuildInputs =
with darwin.apple_sdk.frameworks;
[
Accelerate
CoreVideo
CoreGraphics
]
++ optionals useMetalKit [ MetalKit ];
cudaBuildInputs = with cudaPackages; [
cuda_cudart
cuda_cccl # <nv/target>
libcublas
];
rocmBuildInputs = with rocmPackages; [
clr
hipblas
rocblas
];
vulkanBuildInputs = [
vulkan-headers
vulkan-loader
shaderc
spirv-headers
];
in
effectiveStdenv.mkDerivation (finalAttrs: {
pname = "llama-cpp${pnameSuffix}";
version = llamaVersion;
# Note: none of the files discarded here are visible in the sandbox or
# affect the output hash. This also means they can be modified without
# triggering a rebuild.
src = lib.cleanSourceWith {
filter =
name: type:
let
noneOf = builtins.all (x: !x);
baseName = baseNameOf name;
in
noneOf [
(lib.hasSuffix ".nix" name) # Ignore *.nix files when computing outPaths
(lib.hasSuffix ".md" name) # Ignore *.md changes whe computing outPaths
(lib.hasPrefix "." baseName) # Skip hidden files and directories
(baseName == "flake.lock")
];
src = lib.cleanSource ../../.;
};
# Builds the webui locally, taking care not to require updating any sha256 hash.
webui = stdenvNoCC.mkDerivation {
pname = "webui";
version = llamaVersion;
src = lib.cleanSource ../../tools/ui;
nativeBuildInputs = [
nodejs
importNpmLock.linkNodeModulesHook
];
# no sha256 required when using buildNodeModules
npmDeps = importNpmLock.buildNodeModules {
npmRoot = ../../tools/ui;
inherit nodejs;
};
installPhase = ''
LLAMA_UI_OUT_DIR=$out npm run build --offline
'';
};
postPatch = lib.optionalString useWebUi ''
cp -r ${finalAttrs.webui} tools/ui/dist
chmod -R u+w tools/ui/dist
'';
# With PR#6015 https://github.com/ggml-org/llama.cpp/pull/6015,
# `default.metallib` may be compiled with Metal compiler from XCode
# and we need to escape sandbox on MacOS to access Metal compiler.
# `xcrun` is used find the path of the Metal compiler, which is varible
# and not on $PATH
# see https://github.com/ggml-org/llama.cpp/pull/6118 for discussion
__noChroot = effectiveStdenv.isDarwin && useMetalKit && precompileMetalShaders;
nativeBuildInputs =
[
cmake
ninja
pkg-config
git
]
++ optionals useCuda [
cudaPackages.cuda_nvcc
autoAddDriverRunpath
]
++ optionals (effectiveStdenv.hostPlatform.isGnu && enableStatic) [ glibc.static ]
++ optionals (effectiveStdenv.isDarwin && useMetalKit && precompileMetalShaders) [ xcrunHost ];
buildInputs =
optionals effectiveStdenv.isDarwin darwinBuildInputs
++ optionals useCuda cudaBuildInputs
++ optionals useMpi [ mpi ]
++ optionals useRocm rocmBuildInputs
++ optionals useBlas [ blas ]
++ optionals useVulkan vulkanBuildInputs
++ [ openssl ];
cmakeFlags =
[
(cmakeBool "LLAMA_BUILD_SERVER" true)
(cmakeBool "LLAMA_BUILD_WEBUI" useWebUi)
(cmakeBool "BUILD_SHARED_LIBS" (!enableStatic))
(cmakeBool "CMAKE_SKIP_BUILD_RPATH" true)
(cmakeBool "GGML_NATIVE" false)
(cmakeBool "GGML_BLAS" useBlas)
(cmakeBool "GGML_CUDA" useCuda)
(cmakeBool "GGML_HIP" useRocm)
(cmakeBool "GGML_METAL" useMetalKit)
(cmakeBool "GGML_VULKAN" useVulkan)
(cmakeBool "GGML_STATIC" enableStatic)
(cmakeBool "GGML_RPC" useRpc)
]
++ optionals useCuda [
(
with cudaPackages.flags;
cmakeFeature "CMAKE_CUDA_ARCHITECTURES" (
builtins.concatStringsSep ";" (map dropDot cudaCapabilities)
)
)
]
++ optionals useRocm [
(cmakeFeature "CMAKE_HIP_COMPILER" "${rocmPackages.llvm.clang}/bin/clang")
(cmakeFeature "CMAKE_HIP_ARCHITECTURES" rocmGpuTargets)
]
++ optionals useMetalKit [
(lib.cmakeFeature "CMAKE_C_FLAGS" "-D__ARM_FEATURE_DOTPROD=1")
(cmakeBool "GGML_METAL_EMBED_LIBRARY" (!precompileMetalShaders))
];
# Environment variables needed for ROCm
env = optionalAttrs useRocm {
ROCM_PATH = "${rocmPackages.clr}";
HIP_DEVICE_LIB_PATH = "${rocmPackages.rocm-device-libs}/amdgcn/bitcode";
};
# TODO(SomeoneSerge): It's better to add proper install targets at the CMake level,
# if they haven't been added yet.
postInstall = ''
mkdir -p $out/include
cp $src/include/llama.h $out/include/
'';
meta = {
# Configurations we don't want even the CI to evaluate. Results in the
# "unsupported platform" messages. This is mostly a no-op, because
# cudaPackages would've refused to evaluate anyway.
badPlatforms = optionals useCuda lib.platforms.darwin;
# Configurations that are known to result in build failures. Can be
# overridden by importing Nixpkgs with `allowBroken = true`.
broken = (useMetalKit && !effectiveStdenv.isDarwin);
description = "Inference of LLaMA model in pure C/C++${descriptionSuffix}";
homepage = "https://github.com/ggml-org/llama.cpp/";
license = lib.licenses.mit;
# Accommodates `nix run` and `lib.getExe`
mainProgram = "llama-cli";
# These people might respond, on the best effort basis, if you ping them
# in case of Nix-specific regressions or for reviewing Nix-specific PRs.
# Consider adding yourself to this list if you want to ensure this flake
# stays maintained and you're willing to invest your time. Do not add
# other people without their consent. Consider removing people after
# they've been unreachable for long periods of time.
# Note that lib.maintainers is defined in Nixpkgs, but you may just add
# an attrset following the same format as in
# https://github.com/NixOS/nixpkgs/blob/f36a80e54da29775c78d7eff0e628c2b4e34d1d7/maintainers/maintainer-list.nix
maintainers = with lib.maintainers; [
philiptaron
SomeoneSerge
];
# Extend `badPlatforms` instead
platforms = lib.platforms.all;
};
})
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