Changes
- Replace
use_flash_attention_2
/use_eager_attention
with a unifiedattn_implementation
in the Transformers loader - Ignore
add_bos_token
in instruct prompts, let the jinja2 template decide - Add a "None" option for the speculative decoding model
Backend updates
- Update llama.cpp to https://github.com/ggml-org/llama.cpp/tree/90083283ec254fa8d33897746dea229aee401b37
- Update Transformers to 4.53
- Also update bitsandbytes/Accelerate/PEFT to the latest versions
- Update ExLlamaV3 to 0.0.5
- Update ExLlamaV2 to 0.3.2
Portable builds
Below you can find portable builds: self-contained packages that work with GGUF models (llama.cpp) and require no installation! Just download the right version for your system, unzip, and run.
Which version to download:
-
Windows/Linux:
- NVIDIA GPU: Use
cuda12.4
for newer GPUs orcuda11.7
for older GPUs and systems with older drivers. - AMD/Intel GPU: Use
vulkan
builds. - CPU only: Use
cpu
builds.
- NVIDIA GPU: Use
-
Mac:
- Apple Silicon: Use
macos-arm64
. - Intel CPU: Use
macos-x86_64
.
- Apple Silicon: Use
Updating a portable install:
- Download and unzip the latest version.
- Replace the
user_data
folder with the one in your existing install. All your settings and models will be moved.