Created
May 6, 2025 14:04
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A simple script to convert NeMo Parakeet weights to MLX.
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| import torch | |
| from safetensors.torch import save_file | |
| INPUT_NAME = "model_weights.ckpt" | |
| OUTPUT_NAME = "model.safetensors" | |
| state = torch.load(INPUT_NAME, map_location="cpu") | |
| new_state = {} | |
| for key, value in state.items(): | |
| if key.startswith("preprocessor"): continue | |
| if 'num_batches_tracked' in key: continue | |
| if 'conv' in key or 'ctc_decoder' in key or key == "decoder.decoder_layers.0.weight": | |
| if len(value.shape) == 4: | |
| value = value.permute((0, 2, 3, 1)) | |
| elif len(value.shape) == 3: | |
| value = value.permute((0, 2, 1)) | |
| if 'weight_ih_l' in key: | |
| key = key.replace('weight_ih_l', '') + '.Wx' | |
| if 'weight_hh_l' in key: | |
| key = key.replace('weight_hh_l', '') + '.Wh' | |
| if 'bias_ih_l' in key or 'bias_hh_l' in key: | |
| key = key.replace('bias_ih_l', '').replace('bias_hh_l', '') + '.bias' | |
| new_state[key] = value if new_state.get(key) is None else value + new_state[key] | |
| else: | |
| new_state[key] = value | |
| save_file(new_state, OUTPUT_NAME) |
Author
I am new to conversions, how are you figuring out the conversion parameters?
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Encoder part would work correctly, but decoder part is completely different (Canary is transformer decoder like Whisper) and won't work!