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README.md

+# GLM-ASR-Nano
+## 论文
+[Fun-ASR Technical Report](https://arxiv.org/abs/2509.12508)
+
+## 模型简介
+**GLM-ASR-Nano-2512** 是一款鲁棒的开源语音识别模型，参数量为 **1.5B**。
+该模型专为应对真实世界的复杂场景而设计，在多项基准测试中超越 OpenAI Whisper V3，同时保持紧凑的模型规模。
+
+核心能力包括：
+
+- **卓越的方言支持**
+  除标准普通话和英语外，模型针对**粤语**及其他方言进行了深度优化，有效填补了方言语音识别领域的空白。
+
+- **低音量语音鲁棒性**
+  专门针对**"低语/轻声"**场景进行训练，能够捕捉并准确转录传统模型难以识别的极低音量音频。
+
+- **SOTA 性能**
+  在同类开源模型中实现**最低平均错误率 (4.10)**，在中文基准测试（Wenet Meeting、Aishell-1 等）中展现出显著优势。
+
+<div align=center>
+    <img src="./doc/bench.png"/>
+</div>
+
+## 环境依赖
+
+| 软件 | 版本 |
+| :------: | :------: |
+| DTK | 25.04.2 |
+| python | 3.10.12 |
+| transformers | 5.0.0.dev0 |
+| fastpt | 2.1.1+das.dtk25042 |
+| torch | 2.5.1+das.opt1.dtk25042 |
+| torchaudio | 2.5.1+das.opt1.dtk25042 |
+
+推荐使用镜像: harbor.sourcefind.cn:5443/dcu/admin/base/vllm:0.9.2-ubuntu22.04-dtk25.04.2-tx-1226-das1.7-py3.10-20251226
+
+- 挂载地址`-v`根据实际模型情况修改
+
+```bash
+docker run -it \
+    --shm-size 60g \
+    --network=host \
+    --name glm-asr-nano \
+    --privileged \
+    --device=/dev/kfd \
+    --device=/dev/dri \
+    --device=/dev/mkfd \
+    --group-add video \
+    --cap-add=SYS_PTRACE \
+    --security-opt seccomp=unconfined \
+    -u root \
+    -v /opt/hyhal/:/opt/hyhal/:ro \
+    -v /path/your_code_data/:/path/your_code_data/ \
+    harbor.sourcefind.cn:5443/dcu/admin/base/vllm:0.9.2-ubuntu22.04-dtk25.04.2-tx-1226-das1.7-py3.10-20251226 bash
+```
+更多镜像可前往[光源](https://sourcefind.cn/#/service-list)下载使用。
+
+关于本项目DCU显卡所需的特殊深度学习库可从[光合](https://developer.sourcefind.cn/tool/)开发者社区下载安装，其它包参照requirements.txt安装：
+
+```bash
+pip install -r requirements.txt
+sudo apt update && sudo apt upgrade -y
+apt install ffmpeg
+source fastpt -E  # torchaudio 所需环境，不执行会报错 OSError: libtorch_cuda.so: cannot open shared object file: No such file or directory
+```
+
+## 数据集
+`暂无`
+
+## 训练
+`暂无`
+
+## 推理
+### transformers
+#### 单机推理
+- repo_id: 模型实际地址，当前默认为 `ZhipuAI/GLM-ASR-Nano-2512`，根据实际情况修改
+- audio_url: 测试音频文件地址，当前模型为 `examples/example_zh.wav`, 根据实际情况修改
+
+```bash
+python inference.py
+```
+
+## 效果展示
+
+<div align=center>
+    <img src="./doc/results.png"/>
+</div>
+
+### 精度
+`DCU与GPU精度一致，推理框架：pytorch。`
+
+## 预训练权重
+| 模型名称  | 权重大小  | DCU型号  | 最低卡数需求 |下载地址|
+|:-----:|:----------:|:----------:|:---------------------:|:----------:|
+| GLM-ASR-Nano-2512 | 1.5B | BW1000 | 1 | [Modelscope](https://modelscope.cn/models/ZhipuAI/GLM-ASR-Nano-2512) |
+
+## 源码仓库及问题反馈
+- https://developer.sourcefind.cn/codes/modelzoo/glm-asr-nano_pytorch
+
+## 参考资料
+- https://github.com/zai-org/GLM-ASR

inference.py

+from transformers import AutoModel, AutoProcessor
+import torch
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+repo_id = "ZhipuAI/GLM-ASR-Nano-2512"
+
+processor = AutoProcessor.from_pretrained(repo_id)
+model = AutoModel.from_pretrained(repo_id, dtype=torch.bfloat16, device_map=device)
+
+audio_url = "examples/example_zh.wav"
+
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {
+                "type": "audio",
+                "url": audio_url,
+            },
+            {"type": "text", "text": "Please transcribe this audio into text"},
+        ],
+    }
+]
+
+inputs = processor.apply_chat_template(
+    messages, tokenize=True, add_generation_prompt=True, return_dict=True, return_tensors="pt"
+)
+inputs = inputs.to(device, dtype=torch.bfloat16)
+outputs = model.generate(**inputs, max_new_tokens=128, do_sample=False)
+print(processor.batch_decode(outputs[:, inputs.input_ids.shape[1]:], skip_special_tokens=True))
\ No newline at end of file

model.properties

+# 模型唯一标识
+modelCode=1956
+# 模型名称
+modelName=GLM-ASR-Nano_pytorch
+# 模型描述
+modelDescription=GLM-ASR-Nano-2512是一款鲁棒的开源语音识别模型，参数量为1.5B。
+# 运行过程
+processType=推理
+# 算法类别
+appCategory=语音识别
+# 框架类型
+frameType=pytorch
+# 加速卡类型
+accelerateType=BW1000

requirements.txt

+git+https://github.com/huggingface/transformers
+librosa
\ No newline at end of file