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Carlexxx
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[Sincronização Automática] - 2025-09-23 16:45:24
Browse files- requirements.txt +1 -1
- start.sh +0 -15
requirements.txt
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opencv-python>=4.9.0.80
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torchao
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transformers
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accelerate
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safetensors
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einops
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opencv-python>=4.9.0.80
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torchao
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transformers>=4.47.2,<4.52.0
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accelerate
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safetensors
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einops
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start.sh
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# =============================================================================
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set -euo pipefail
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# 2. Instala a wheel pré-compilada do Flash Attention 2.8.0
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# Esta é a forma mais rápida e estável de instalar, evitando compilação demorada.
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# Esta wheel é compatível com PyTorch 2.8.0 e CUDA 12.x
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RUN git clone https://github.com/Dao-AILab/flash-attention && \
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cd flash-attention/hopper && \
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pip -v setup.py install && \
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export PYTHONPATH=$PWD && \
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pytest -q -s test_flash_attn.py
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# 3. Compila e instala o NVIDIA Apex
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RUN git clone https://github.com/NVIDIA/apex.git && \
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cd apex && \
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pip install -v --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./ && \
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cd .. && rm -rf apex
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# 4. Instala os Kernels customizados do LTX
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RUN pip -v install --no-build-isolation git+https://github.com/Lightricks/LTX-Video-Q8-Kernels.git
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# =============================================================================
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set -euo pipefail
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# 4. Instala os Kernels customizados do LTX
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RUN pip -v install --no-build-isolation git+https://github.com/Lightricks/LTX-Video-Q8-Kernels.git
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