Instructions to use Retrieve0/Qwen3-ASR-1.7B-TensorRT-Encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TensorRT
How to use Retrieve0/Qwen3-ASR-1.7B-TensorRT-Encoder with TensorRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
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Download README.md from Retrieve0/Qwen3-ASR-1.7B-TensorRT-Encoder: direct link, hf CLI and curl.
- Browser
- Download file 4.3 kB
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https://huggingface.co/Retrieve0/Qwen3-ASR-1.7B-TensorRT-Encoder/resolve/main/README.md
- Command line
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hf download hf://Retrieve0/Qwen3-ASR-1.7B-TensorRT-Encoder/README.md
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curl -L -o README.md https://huggingface.co/Retrieve0/Qwen3-ASR-1.7B-TensorRT-Encoder/resolve/main/README.md
4.3 kB
| license: apache-2.0 | |
| base_model: Qwen/Qwen3-ASR-1.7B-hf | |
| library_name: onnxruntime | |
| pipeline_tag: automatic-speech-recognition | |
| tags: | |
| - qwen3-asr | |
| - tensorrt | |
| - onnx | |
| - bf16 | |
| - fp16 | |
| <p align="center"> | |
| <a href="https://github.com/lost0427/Qwen3-ASR-TensorRT"><img src="https://img.shields.io/badge/GitHub-source-181717?logo=github" alt="GitHub source"></a> | |
| <a href="https://huggingface.co/Retrieve0/Qwen3-ASR-1.7B-TensorRT-Encoder"><img src="https://img.shields.io/badge/Hugging_Face-model-yellow?logo=huggingface" alt="Hugging Face model"></a> | |
| </p> | |
| # Qwen3-ASR 1.7B TensorRT Encoder | |
| ## English | |
| ONNX exports of the audio encoder from [Qwen/Qwen3-ASR-1.7B-hf](https://huggingface.co/Qwen/Qwen3-ASR-1.7B-hf), prepared for TensorRT inference. Use an encoder export with a compatible Qwen3-ASR text decoder, such as the [EXL3 decoder](https://huggingface.co/Retrieve0/Qwen3-ASR-1.7B-EXL3-Decoder). The [Qwen3-ASR-TensorRT repository](https://github.com/lost0427/Qwen3-ASR-TensorRT) integrates the encoder and decoder for transcription. | |
| ### Files | |
| | Precision | Files | Use | | |
| | --- | --- | --- | | |
| | BF16 | `encoder-window.bf16.onnx`, `encoder-window.bf16.onnx.data` | Reference export for GPUs with BF16 support | | |
| | FP16 | `encoder-window.fp16.onnx`, `encoder-window.fp16.onnx.data` | Compatibility export for older NVIDIA GPUs | | |
| TensorRT `.engine` files are not included because they depend on the target GPU architecture and TensorRT build environment. Build an engine locally with this project. | |
| ### Precision and calibration | |
| BF16 is the project reference precision. FP16 supports NVIDIA GPUs without BF16. This repository publishes the BF16 and FP16 encoder exports. | |
| ### Requirements | |
| - NVIDIA GPU and CUDA | |
| - Reference environment: CUDA 12.8, TensorRT 11.4.0.106, Python 3.10–3.13 | |
| - The [Qwen3-ASR-TensorRT repository](https://github.com/lost0427/Qwen3-ASR-TensorRT), which includes the encoder/decoder integration | |
| Windows is tested and supported. Linux should work with compatible CUDA, TensorRT, PyTorch, and ExLlamaV3 packages. | |
| ### Build | |
| ```powershell | |
| uv sync --extra quantization | |
| uv run qwen3-asr --model Qwen/Qwen3-ASR-1.7B-hf build --encoder-precision bf16 | |
| uv run qwen3-asr --model Qwen/Qwen3-ASR-1.7B-hf build --encoder-precision fp16 | |
| ``` | |
| ### License and citation | |
| This export is derived from `Qwen/Qwen3-ASR-1.7B-hf` and is published under Apache-2.0. Retain the upstream attribution and license. Please also cite the Qwen3-ASR work and the runtime project. | |
| ## 中文 | |
| 本仓库提供 [Qwen/Qwen3-ASR-1.7B-hf](https://huggingface.co/Qwen/Qwen3-ASR-1.7B-hf) 音频编码器的 ONNX 导出,可用于 TensorRT 推理。使用时需配套兼容的 Qwen3-ASR 文本解码器,例如 [EXL3 解码器](https://huggingface.co/Retrieve0/Qwen3-ASR-1.7B-EXL3-Decoder)。[Qwen3-ASR-TensorRT 仓库](https://github.com/lost0427/Qwen3-ASR-TensorRT)已集成 encoder 和 decoder,可用于完整转写。 | |
| ### 文件 | |
| | 精度 | 文件 | 用途 | | |
| | --- | --- | --- | | |
| | BF16 | `encoder-window.bf16.onnx`、`encoder-window.bf16.onnx.data` | 支持 BF16 的 GPU 上的基准导出 | | |
| | FP16 | `encoder-window.fp16.onnx`、`encoder-window.fp16.onnx.data` | 兼容不支持 BF16 的较旧 NVIDIA GPU | | |
| 本仓库不提供 TensorRT `.engine` 文件,因为它们依赖目标 GPU 架构和 TensorRT 构建环境。请在目标设备上使用本项目构建 engine。 | |
| ### 精度与校准 | |
| BF16 是本项目的基准精度,FP16 用于不支持 BF16 的 NVIDIA GPU。本仓库发布 BF16 和 FP16 encoder 导出文件。 | |
| ### 运行要求 | |
| - NVIDIA GPU 与 CUDA | |
| - 参考环境:CUDA 12.8、TensorRT 11.4.0.106、Python 3.10–3.13 | |
| - [Qwen3-ASR-TensorRT 仓库](https://github.com/lost0427/Qwen3-ASR-TensorRT),其中已包含 encoder/decoder 集成 | |
| 项目已在 Windows 上测试并可用。Linux 环境在 CUDA、TensorRT、PyTorch 和 ExLlamaV3 软件包版本兼容时也可运行。 | |
| ### 构建 | |
| ```powershell | |
| uv sync --extra quantization | |
| uv run qwen3-asr --model Qwen/Qwen3-ASR-1.7B-hf build --encoder-precision bf16 | |
| uv run qwen3-asr --model Qwen/Qwen3-ASR-1.7B-hf build --encoder-precision fp16 | |
| ``` | |
| ### 许可证与引用 | |
| 本导出基于 `Qwen/Qwen3-ASR-1.7B-hf`,以 Apache-2.0 发布。请保留上游归属说明和许可证,并引用 Qwen3-ASR 工作及本运行时项目。 | |