llama-core
This is a solo llama connector also; being able to work independently.
install via (pip/pip3):
pip install llama-core
run it by (python/python3):
python -m llama_core
Prompt to user interface selection menu above; while chosen, GGUF file(s) in the current directory will be searched and detected (if any) as below.
include interface selector to your code by adding:
from llama_core import menu
include gguf reader to your code by adding:
from llama_core import reader
include gguf writer to your code by adding:
from llama_core import writer
remark(s)
OOther functions are same as llama-cpp-python; for CUDA(GPU, Nvida) and Metal(M1/M2/M3, Apple) supported settings, please specify CMAKE_ARGS following Abetlen's repo below; if you want to install it by source file (under releases), you should opt to do it by .tar.gz file (then build your machine-customized installable package) rather than .whl (wheel; a pre-built binary package) with an appropriate cmake tag(s).
references
repo llama-cpp-python llama.cpp page gguf.us
build from llama_core-(version).tar.gz (examples for CPU setup below)
According to the latest note inside vs code, msys64 was recommended by Microsoft; or you could opt w64devkit or etc. as source/location of your gcc and g++ compilers.
for windows user(s):
$env:CMAKE_GENERATOR = "MinGW Makefiles"
$env:CMAKE_ARGS = "-DCMAKE_C_COMPILER=C:/msys64/mingw64/bin/gcc.exe -DCMAKE_CXX_COMPILER=C:/msys64/mingw64/bin/g++.exe"
pip install llama_core-(version).tar.gz
In mac, xcode command line tools were recommended by Apple for dealing all coding related issue(s); or you could bypass it for your own good/preference.
for mac user(s):
pip3 install llama_core-(version).tar.gz
for high (just a little bit better) performance seeker(s):
example setup for metal (M1/M2/M3 - Apple) - faster
CMAKE_ARGS="-DGGML_METAL=on" pip3 install llama_core-(version).tar.gz
example setup for cuda (GPU - Nvida) - faster x2; depends on your model (how rich you are)
CMAKE_ARGS="-DGGML_CUDA=on" pip install llama_core-(version).tar.gz
make sure your gcc and g++ are >=11; you can check it by: gcc --version and g++ --version; other setting(s) include: cmake>=3.21, etc.; however, if you opt to install it by the pre-built wheel (.whl) file then you don't need to worry about that.
1 maintainer
Metadata
1 maintainer
Release files for llama-core 0.4.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| llama_core-0.4.2.tar.gz | 67.6 MB | Without provenance | Details |
Built distributions (wheels)
| File | Reset | |||
|---|---|---|---|---|
| llama_core-0.4.2-cp313-cp313-macosx_15_0_arm64.whl | CPython 3.13 | CPython 3.13 | macOS 15.0+ ARM64 | Details |
| llama_core-0.4.2-cp312-cp312-macosx_15_0_arm64.whl | CPython 3.12 | CPython 3.12 | macOS 15.0+ ARM64 | Details |
| llama_core-0.4.2-cp312-cp312-macosx_11_0_x86_64.whl | CPython 3.12 | CPython 3.12 | macOS 11.0+ x86-64 | Details |
| llama_core-0.4.2-cp311-cp311-win_amd64.whl | CPython 3.11 | CPython 3.11 | Windows x86-64 | Details |
| llama_core-0.4.2-cp311-cp311-macosx_15_0_arm64.whl | CPython 3.11 | CPython 3.11 | macOS 15.0+ ARM64 | Details |
Total release size: 95.0 MB
Release files / llama_core-0.4.2.tar.gz
| Download URL | llama_core-0.4.2.tar.gz |
|---|---|
| Size | 67.6 MB |
| Tags | Source |
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|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.4
|
Release files / llama_core-0.4.2-cp313-cp313-macosx_15_0_arm64.whl
| Download URL | llama_core-0.4.2-cp313-cp313-macosx_15_0_arm64.whl |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.4
|
Release files / llama_core-0.4.2-cp312-cp312-macosx_15_0_arm64.whl
| Download URL | llama_core-0.4.2-cp312-cp312-macosx_15_0_arm64.whl |
|---|---|
| Size | 5.7 MB |
| Tags | CPython 3.12 macOS 15.0+ ARM64 |
|
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No |
| Uploaded via |
twine/4.0.2 CPython/3.11.4
|
Release files / llama_core-0.4.2-cp312-cp312-macosx_11_0_x86_64.whl
| Download URL | llama_core-0.4.2-cp312-cp312-macosx_11_0_x86_64.whl |
|---|---|
| Size | 6.5 MB |
| Tags | CPython 3.12 macOS 11.0+ x86-64 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.4
|
Release files / llama_core-0.4.2-cp311-cp311-win_amd64.whl
| Download URL | llama_core-0.4.2-cp311-cp311-win_amd64.whl |
|---|---|
| Size | 3.8 MB |
| Tags | CPython 3.11 Windows x86-64 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.4
|
Release files / llama_core-0.4.2-cp311-cp311-macosx_15_0_arm64.whl
| Download URL | llama_core-0.4.2-cp311-cp311-macosx_15_0_arm64.whl |
|---|---|
| Size | 5.7 MB |
| Tags | CPython 3.11 macOS 15.0+ ARM64 |
|
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.4
|
Security for llama-core 0.4.2
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