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🧨 Stable Diffusion in JAX / Flax !
Read the full article🧨 Stable Diffusion in JAX / Flax ! on Hugging Face
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🧨 Stable Diffusion in JAX / Flax !
Fordel's Take
Moving Stable Diffusion to JAX/Flax is cool for the hardcore folks, but honestly, it just means we're trading one set of framework headaches for another. The complexity of managing distributed training and compiler optimizations just multiplies the debugging time. It's technically cleaner, sure, but it doesn't magically fix the fundamental problem of deploying and scaling massive diffusion models efficiently.
What To Do
Only adopt JAX/Flax if your team already has deep expertise in distributed ML programming; otherwise, stick to PyTorch where the ecosystem is less fragmented.
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