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Support MLX in WhisperAX #200
base: mlx-support
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…lity (#192) * Make additional initializers, functions, members public, for WKPro * Allows use of default internal functions & member accesses which have increased protections when imported * Initializers were Xcode generated: right click class name -> refactor -> generate memberwise initializers * memberwise initializer defaults to internal, mark as public. * Formatting --------- Co-authored-by: ZachNagengast <[email protected]>
… models (#193) * Add initial mlpackage loading (if .mlmodelc not present) -- Does not modify model loading in OS WK. This is a hook to modify load path URLs. * Always load audio encoder last * Adjust timings to account for decoder<>encoder order swap * Add helper for mlpackage detection --------- Co-authored-by: ZachNagengast <[email protected]>
* Fix start time logic for file loading and resampling * Add test file
As far as I can tell, these stored properties are not meant to be changed. Therefore, change them to be immutable. This change also makes these static properties concurrency-safe.
* Add VoiceActivityDetector base class Add base class to allow different VAD implementations * fix spaces
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LGTM, added some comments, let me know what you think
======= | ||
>>>>>>> main |
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git conflict markers
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Ah good catch 👍
Package.resolved
Outdated
"location" : "https://github.com/ml-explore/mlx-swift", | ||
"location" : "https://github.com/davidkoski/mlx-swift.git", | ||
"state" : { | ||
"revision" : "597aaa5f465b4b9a17c8646b751053f84e37925b", | ||
"version" : "0.16.0" | ||
"revision" : "3314bc684f0ccab1793be54acddaea16c0501d3c" |
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curious, why this change?
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ok, now I can see why, nvm
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This has been merged into mlx-swift and tagged 0.16.2
@@ -171,6 +137,74 @@ public struct ModelComputeOptions { | |||
} | |||
} | |||
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public struct ModelInfo: Identifiable, Hashable { | |||
public let id = UUID() |
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curious, why this property public let id = UUID()
is needed? can it be uniquely identified by name?
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Needed to make it identifiable, although I was using this for the picker at one point and may be vestigial, will check.
let keyCache = try? MLX.stacked(keyCacheResult).asMLMultiArray() | ||
let valueCache = try? MLX.stacked(valueCacheResult).asMLMultiArray() | ||
let decodingCache = DecodingCache( | ||
keyCache: keyCache, | ||
valueCache: valueCache, | ||
alignmentWeights: nil | ||
) | ||
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let logits = try? result.logits?.asMLMultiArray() |
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seems like you've changed it to try ?
in couple of places, is it intended?
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Good point, we want this to pass the throw up through the call stack. Reviewing build warnings as well.
that fork was merged and is now the |
Awesome, thanks for the update @davidkoski! |
@ZachNagengast - This looks awesome! Apologies - rookie question... It looks like currently the MLX repo only has the base and tiny models. How hard is it for mere mortals to "build" some of the larger models for testing this out with larger models? |
Or... can you use existing models with MLX? |
Sorry missed your original message! We will fill in the mlx repo with the remaining models as part of this release, we just made these copies for consistency with our swift package. Any MLX whisper model currently existing with the same naming scheme will work in theory 👍 @jkrukowski may be able to confirm or deny. |
Legend, thanks @ZachNagengast! So basically, we do need new models for MLX, we can use the existing WhisperKit models? They need to be optimised or something? |
Yep the existing WhisperKit models are optimized for CoreML, the ones in this repo we will fill out with the equivalent weights that are compatible with this MLX PR |
Sorry for all the rookie questions, but when you say "optimised for CoreML" - does this mean they ONLY work on CoreML, or can you use these CoreML models in MLX and they're just not as fast/accurate? Apologies - this whole Whisper world is very new to me, so I very much appreciate all your wisdom and support! |
@ZachNagengast Is there any model conversion script we can run, or any other source we can use, in order to create/obtain more MLX compatible model versions? |
@latenitefilms Yes the .mlmodelc models only work with CoreML at the moment. |
Legend, thanks so much @ZachNagengast! Do you have a rough/ballpark ETA of when you're hoping to finish and merge in MLX support? No rush or pressure - just wondering if it's worth trying to convert our own models or not. Let me know if there's anything I can do to help with MLX testing/release! Would love to see this in action ASAP! Thanks for EVERYTHING you do! Appreciate it! |
There are just a few optimizations to fix up to make it ready for release, specifically memory usage. Current issues are:
These are paraphrased from @davidkoski and @awni Will be revisiting this after the upcoming release but feel free to test with this current branch if you see any other potential speedup besides these, all the interfaces should be the same in its final form, just faster and more memory efficient with these changes. |
Amazing! Thanks so much! Will test out and let you know if I break anything. |
Any update on this? Is it usable? @latenitefilms @ZachNagengast ? Can someone please point me in the direction of how i can get this set up? |
Hi @anishjain123 these are still pending issues #200 (comment), but this branch is technically usable. We'd like to resolve the perf and memory issues before merging, which is still a high priority for us! Working on a refactor right now to allow various different model input and output types, including MLXArray, which should help with the issues converting between MLMultiArray and MLXArray. |
Add support for the WhisperAX example app, as well as various refactors and cleanup.
Note: this is using an unreleased version of MLX, pending merge of ml-explore/mlx-swift#130
There are still some memory issues to address, will look more into this soon.
CoreML:
MLX:
Important note, first time running this will likely throw an error about PrepareMetalShaders, which requires Trust & Enable on this popup when selecting the error.