Comments (1)
The issue is that burn-wgpu doesn't currently use the maximum available device memory limits so larger models may fail to run. I'm hoping to resolve this within the next day or two. The slow model loading speed should be resolved by the latest updates.
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Related Issues (20)
- bug: transcribing with medium model HOT 4
- run by example encounted failure HOT 1
- No output with 8 second clip? HOT 3
- Panic while transcribing audio.wav HOT 1
- Can not choose second gpu using wgpu HOT 2
- Changes to run on CUDA with TchBackend HOT 4
- Garbage output on multi channel audio and audio above 24khz HOT 4
- Muffled Text - Response for Custom Audio HOT 1
- Does using wgpu backend requires Torch to be installed? HOT 1
- Tinygrad import path changed in model conversion script HOT 1
- Trouble importing finetuned HuggingFace model HOT 12
- Trying the example I got an empty transcription HOT 12
- Tinygrad dependancy for weights conversion HOT 1
- Python issues HOT 1
- WGPU issues in Macbook M1 HOT 5
- FR: sorta. Consider splitting out speech preprocessing into a separate crate
- Assistance with creating a French configuration for whisper-burn
- When using repo as library, incorrect version of burn gets used, adding version tag to cargo.toml may fix
- Use Burn's PyTorchFileRecoder to Directly Load PyTorch Model
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