MLX-native int8 conversion of Qwen3-ASR-1.7B for local automatic speech recognition on Apple Silicon — English, Chinese, and mixed Chinese/English. It runs through the mlx-speech runtime with no PyTorch and no cloud API at inference time. Weights ship as plain.safetensors. Install mlx-speech, then load by alias (downloads on first use): Or download the weights once and load by local path: - This repo contains the quantized MLX runtime artifact only. - The quantization mode (affine, groupsize 64, 8-bit) is stored in config.json and re-applied automatically on load, so it cannot desync from the weights. - v0 is single-pass offline ASR; streaming, timestamps, and long-audio chunking are…
Open weights
apache-2.0
2.4B parameters
mlx
This repository contains a self-contained pure-MLX int8 conversion of Step-Audio-EditX for local voice cloning and expressive audio editing on Apple Silicon. All pipeline components are stored as.safetensors — no PyTorch, ONNX, or NumPy files are required at inference time. This bundle is self-contained — all weights are packaged in one repository. Five-stage pipeline, all running pure MLX with bf16 activations: 1. Step1 LM (3.5B params, int8) — autoregressive dual-codebook token generation 2. CampPlus (bf16) — speaker embedding extraction from reference audio 3. Flow conditioner (bf16) — conditions generation on speaker embedding 4. Flow model (int8) — flow-matching mel spectrogram…
Open weights
apache-2.0
3.5B parameters
mlx
Pure-MLX selective-int8 conversion of IBM's for local automatic speech recognition on Apple Silicon. The complete waveform-to-text runtime uses mlx-speech; PyTorch, Transformers, mlx-audio, vLLM, and cloud APIs are not runtime dependencies. Portuguese, and Japanese The Granite causal language model uses 8-bit affine weight quantization with group size 64. The acoustic encoder, QFormer projector, normalization, convolution, biases, activations, and KV cache retain BF16 precision. The exact quantization contract is stored in config.json, and the runtime reconstructs the saved quantized module set from checkpoint.scales tensors before strict weight loading. BF16/int8 checks used two 12–13…
Open weights
apache-2.0
2.3B parameters
4,096 tokens
mlx
MLX-native bf16 conversion of Qwen3-ASR-1.7B for local automatic speech recognition on Apple Silicon — English, Chinese, and mixed Chinese/English. It runs through the mlx-speech runtime with no PyTorch and no cloud API at inference time. Weights ship as plain.safetensors. Install mlx-speech, then load by alias (downloads on first use): Or download the weights once and load by local path: - This repo contains the MLX runtime artifact only (no PyTorch checkpoint). - v0 is single-pass offline ASR; streaming, timestamps, and long-audio chunking are deferred. - For a smaller download, use the int8 build. Apache 2.0, following the upstream Qwen3-ASR release. Refer to the original Qwen release…
Open weights
apache-2.0
2.3B parameters
mlx
Multilingual voice cloning on Apple audio This repository brings mlx-speech as a complete MLX voice-cloning pipeline. Give it a reference recording, its transcript, and the text you want spoken. It returns a waveform in the reference speaker's voice. App Automaton maintains the MLX conversion and runtime. Speech generation runs locally on your Mac, including speaker conditioning and waveform reconstruction. The current release is Base BF16, stored in base/mlx-bf16/. Each model variant has its own complete inference bundle. Instruct will be added under instruct/ after its MLX pipeline is validated, keeping the Base path stable. Requires an Apple Silicon Mac and Python 3.13 or later. The…
Open weights
apache-2.0
mlx
MLX-native bf16 conversion of NetEase Youdao's Confucius4-R2T2, a streaming speech recognition model finetuned from Qwen3-ASR-1.7B. It runs through the mlx-speech runtime on Apple Silicon with no PyTorch, vLLM, or cloud API at inference time. Streaming — feed microphone PCM as it arrives: Or download once and load by path: mlx-speech implements NetEase's chunk loop: prefix rollback, per-window token budget, and append-only commit. Each window reuses the previous window's mel frames, closed audio-encoder blocks, and decoder KV prefix, and recomputes only what changed. - This repo contains the MLX runtime artifact only (no PyTorch checkpoint). The model weights are licensed under the NetEase…
Open weights
other
2B parameters
mlx
