70 lines
5.7 KiB
Markdown
70 lines
5.7 KiB
Markdown
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# 使用 OpenVINO 部署 GLM-4-9B-Chat 模型
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Read this in [English](README_en.md).
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[OpenVINO](https://www.intel.com/content/www/us/en/developer/tools/openvino-toolkit/overview.html)
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是 Intel 为深度学习推理而设计的开源工具包。它可以帮助开发者优化模型，提高推理性能，减少模型的内存占用。
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本示例将展示如何使用 OpenVINO 部署 GLM-4-9B-Chat 模型。
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## 1. 环境配置
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首先，你需要安装依赖
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```bash
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pip install -r requirements.txt
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```
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## 2. 转换模型
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由于需要将Huggingface模型转换为OpenVINO IR模型，因此您需要下载模型并转换。
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```
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python3 convert.py --model_id THUDM/glm-4-9b-chat --output {your_path}/glm-4-9b-chat-ov
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```
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### 可以选择的参数
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* `--model_id` - 模型所在目录的路径（绝对路径）。
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* `--output` - 转换后模型保存的地址。
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* `--precision` - 转换的精度。
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转换过程如下：
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```
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====Exporting IR=====
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Framework not specified. Using pt to export the model.
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Loading checkpoint shards: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:04<00:00, 2.14it/s]
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Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
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Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
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Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
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Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
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Using framework PyTorch: 2.3.1+cu121
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Mixed-Precision assignment ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 160/160 • 0:01:45 • 0:00:00
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INFO:nncf:Statistics of the bitwidth distribution:
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┍━━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┑
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│ Num bits (N) │ % all parameters (layers) │ % ratio-defining parameters (layers) │
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┝━━━━━━━━━━━━━━━━┿━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┿━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┥
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│ 8 │ 31% (76 / 163) │ 20% (73 / 160) │
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├────────────────┼─────────────────────────────┼────────────────────────────────────────┤
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│ 4 │ 69% (87 / 163) │ 80% (87 / 160) │
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┕━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┙
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Applying Weight Compression ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 163/163 • 0:03:46 • 0:00:00
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Configuration saved in glm-4-9b-ov/openvino_config.json
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====Exporting tokenizer=====
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Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
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```
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## 3. 运行 GLM-4-9B-Chat 模型
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```
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python3 chat.py --model_path {your_path}/glm-4-9b-chat-ov --max_sequence_length 4096 --device CPU
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```
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### 可以选择的参数
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* `--model_path` - OpenVINO IR 模型所在目录的路径。
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* `--max_sequence_length` - 输出标记的最大大小。
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* `--device` - 运行推理的设备。
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### 参考代码
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本代码参考 [OpenVINO 官方示例](https://github.com/OpenVINO-dev-contest/chatglm3.openvino) 进行修改。
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