This commit is contained in:
baalajimaestro 2024-01-26 12:21:14 +05:30
commit c39debbb1e
Signed by: baalajimaestro
GPG key ID: F93C394FE9BBAFD5
6 changed files with 32 additions and 10 deletions

View file

@ -7,6 +7,14 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
## [Unreleased]
## [0.2.33]
- feat: Update llama.cpp to ggerganov/llama.cpp@faa3526a1eba458120987ed8269e5616385a76f4
- feat(server): include llama-cpp-python version in openapi spec by @abetlen in cde7514c3d28e6d52f272614e9957208c344dde5
- fix: use both eos and bos tokens as stop sequences for hf-tokenizer-config chat format. by @abetlen in 5b982d0f8c6f35242c8862ffdce00e17cea0b44f
- fix: GGUF metadata KV overrides, re #1011 by @phiharri in #1116
- fix: llama_log_set should be able to accept null pointer by @abetlen in c970d41a85381fd55235136f123422df0bf0c7e7
## [0.2.32]
- feat: Update llama.cpp to ggerganov/llama.cpp@504dc37be8446fb09b1ede70300250ad41be32a2

View file

@ -104,6 +104,7 @@ CMAKE_ARGS="-DLLAMA_HIPBLAS=on" pip install llama-cpp-python
### Windows Notes
If you run into issues where it complains it can't find `'nmake'` `'?'` or CMAKE_C_COMPILER, you can extract w64devkit as [mentioned in llama.cpp repo](https://github.com/ggerganov/llama.cpp#openblas) and add those manually to CMAKE_ARGS before running `pip` install:
```ps
$env:CMAKE_GENERATOR = "MinGW Makefiles"
$env:CMAKE_ARGS = "-DLLAMA_OPENBLAS=on -DCMAKE_C_COMPILER=C:/w64devkit/bin/gcc.exe -DCMAKE_CXX_COMPILER=C:/w64devkit/bin/g++.exe"
@ -118,17 +119,19 @@ Detailed MacOS Metal GPU install documentation is available at [docs/install/mac
#### M1 Mac Performance Issue
Note: If you are using Apple Silicon (M1) Mac, make sure you have installed a version of Python that supports arm64 architecture. For example:
```
```bash
wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-MacOSX-arm64.sh
bash Miniforge3-MacOSX-arm64.sh
```
Otherwise, while installing it will build the llama.cpp x86 version which will be 10x slower on Apple Silicon (M1) Mac.
#### M Series Mac Error: `(mach-o file, but is an incompatible architecture (have 'x86_64', need 'arm64'))`
Try installing with
```
```bash
CMAKE_ARGS="-DCMAKE_OSX_ARCHITECTURES=arm64 -DCMAKE_APPLE_SILICON_PROCESSOR=arm64 -DLLAMA_METAL=on" pip install --upgrade --verbose --force-reinstall --no-cache-dir llama-cpp-python
```
@ -152,10 +155,15 @@ Below is a short example demonstrating how to use the high-level API to for basi
```python
>>> from llama_cpp import Llama
>>> llm = Llama(model_path="./models/7B/llama-model.gguf")
>>> llm = Llama(
model_path="./models/7B/llama-model.gguf",
# n_gpu_layers=-1, # Uncomment to use GPU acceleration
# seed=1337, # Uncomment to set a specific seed
# n_ctx=2048, # Uncomment to increase the context window
)
>>> output = llm(
"Q: Name the planets in the solar system? A: ", # Prompt
max_tokens=32, # Generate up to 32 tokens
max_tokens=32, # Generate up to 32 tokens, set to None to generate up to the end of the context window
stop=["Q:", "\n"], # Stop generating just before the model would generate a new question
echo=True # Echo the prompt back in the output
) # Generate a completion, can also call create_completion
@ -191,7 +199,10 @@ Note that `chat_format` option must be set for the particular model you are usin
```python
>>> from llama_cpp import Llama
>>> llm = Llama(model_path="path/to/llama-2/llama-model.gguf", chat_format="llama-2")
>>> llm = Llama(
model_path="path/to/llama-2/llama-model.gguf",
chat_format="llama-2"
)
>>> llm.create_chat_completion(
messages = [
{"role": "system", "content": "You are an assistant who perfectly describes images."},
@ -414,6 +425,9 @@ pip install -e .[all]
make clean
```
You can also test out specific commits of `lama.cpp` by checking out the desired commit in the `vendor/llama.cpp` submodule and then running `make clean` and `pip install -e .` again. Any changes in the `llama.h` API will require
changes to the `llama_cpp/llama_cpp.py` file to match the new API (additional changes may be required elsewhere).
## FAQ
### Are there pre-built binaries / binary wheels available?

View file

@ -1,4 +1,4 @@
from .llama_cpp import *
from .llama import *
__version__ = "0.2.32"
__version__ = "0.2.33"

View file

@ -2528,7 +2528,7 @@ _lib.llama_print_system_info.restype = c_char_p
# // If this is not called, or NULL is supplied, everything is output on stderr.
# LLAMA_API void llama_log_set(ggml_log_callback log_callback, void * user_data);
def llama_log_set(
log_callback: "ctypes._FuncPointer", user_data: c_void_p # type: ignore
log_callback: Union["ctypes._FuncPointer", c_void_p], user_data: c_void_p # type: ignore
):
"""Set callback for all future logging events.
@ -2536,7 +2536,7 @@ def llama_log_set(
return _lib.llama_log_set(log_callback, user_data)
_lib.llama_log_set.argtypes = [llama_log_callback, c_void_p]
_lib.llama_log_set.argtypes = [ctypes.c_void_p, c_void_p]
_lib.llama_log_set.restype = None

View file

@ -118,7 +118,7 @@ def create_app(
app = FastAPI(
middleware=middleware,
title="🦙 llama.cpp Python API",
version="0.0.1",
version=llama_cpp.__version__,
)
app.add_middleware(
CORSMiddleware,

2
vendor/llama.cpp vendored

@ -1 +1 @@
Subproject commit 26d607608d794efa56df3bdb6043a2f94c1d632c
Subproject commit faa3526a1eba458120987ed8269e5616385a76f4