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feat/darwi
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e4ea2dcfa8 | ||
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40daa857c7 | ||
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c0efc28968 |
3
.github/backend-matrix.yml
vendored
3
.github/backend-matrix.yml
vendored
@@ -4974,6 +4974,9 @@ includeDarwin:
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- backend: "kitten-tts"
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tag-suffix: "-metal-darwin-arm64-kitten-tts"
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build-type: "mps"
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- backend: "trl"
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tag-suffix: "-metal-darwin-arm64-trl"
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build-type: "mps"
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- backend: "liquid-audio"
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tag-suffix: "-metal-darwin-arm64-liquid-audio"
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build-type: "mps"
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@@ -5295,6 +5295,7 @@
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nvidia: "cuda12-trl"
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nvidia-cuda-12: "cuda12-trl"
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nvidia-cuda-13: "cuda13-trl"
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metal: "metal-trl"
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## TRL backend images
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- !!merge <<: *trl
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name: "cpu-trl"
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@@ -5326,6 +5327,16 @@
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uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-13-trl"
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mirrors:
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- localai/localai-backends:master-gpu-nvidia-cuda-13-trl
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- !!merge <<: *trl
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name: "metal-trl"
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uri: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-trl"
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mirrors:
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- localai/localai-backends:latest-metal-darwin-arm64-trl
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- !!merge <<: *trl
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name: "metal-trl-development"
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uri: "quay.io/go-skynet/local-ai-backends:master-metal-darwin-arm64-trl"
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mirrors:
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- localai/localai-backends:master-metal-darwin-arm64-trl
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## llama.cpp quantization backend
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- &llama-cpp-quantization
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name: "llama-cpp-quantization"
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@@ -8,7 +8,13 @@ else
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source $backend_dir/../common/libbackend.sh
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fi
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EXTRA_PIP_INSTALL_FLAGS+=" --upgrade --index-strategy=unsafe-first-match"
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EXTRA_PIP_INSTALL_FLAGS+=" --upgrade"
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# --index-strategy is a uv-only flag. The darwin/MPS build installs with pip
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# (USE_PIP=true in scripts/build/python-darwin.sh), which rejects it. Only add
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# it when uv is the installer, keeping the Linux/CUDA resolution unchanged.
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if [ "x${USE_PIP:-}" != "xtrue" ]; then
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EXTRA_PIP_INSTALL_FLAGS+=" --index-strategy=unsafe-first-match"
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fi
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installRequirements
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# Fetch convert_hf_to_gguf.py and gguf package from the same llama.cpp version
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12
backend/python/trl/requirements-mps.txt
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12
backend/python/trl/requirements-mps.txt
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@@ -0,0 +1,12 @@
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torch==2.10.0
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trl
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peft
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datasets>=3.0.0
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transformers>=4.56.2
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accelerate>=1.4.0
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huggingface-hub>=1.3.0
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sentencepiece
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# Note: bitsandbytes is intentionally omitted on MPS. It is only used by the
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# CUDA (cublas) variants for 8-bit/4-bit quantization and has poor support on
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# Apple Silicon. torch here uses the plain PyPI wheels, which ship MPS support
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# on macOS arm64.
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