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Model: xiaowangge/minicpm4-8b-gguf Source: Original Platform
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README.md
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---
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frameworks:
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- Pytorch
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license: Apache License 2.0
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tasks:
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- text-generation
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#model-type:
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##如 gpt、phi、llama、chatglm、baichuan 等
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#- gpt
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#domain:
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##如 nlp、cv、audio、multi-modal
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#- nlp
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#language:
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##语言代码列表 https://help.aliyun.com/document_detail/215387.html?spm=a2c4g.11186623.0.0.9f8d7467kni6Aa
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#- cn
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#metrics:
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##如 CIDEr、Blue、ROUGE 等
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#- CIDEr
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#tags:
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##各种自定义，包括 pretrained、fine-tuned、instruction-tuned、RL-tuned 等训练方法和其他
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#- pretrained
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#tools:
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##如 vllm、fastchat、llamacpp、AdaSeq 等
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#- vllm
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language:
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- zh
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- en
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base_model:
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- OpenBMB/MiniCPM4-8B
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base_model_relation: quantized
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---
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### 介绍
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1. 该模型基于 `https://www.modelscope.cn/models/OpenBMB/MiniCPM4-8B` 转换。
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2. 开源许可遵循 `MiniCPM4-8B`。
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### 模型下载
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#### SDK 下载
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```bash
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# 安装 ModelScope
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pip install modelscope
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```
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```python
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# SDK模型下载
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from modelscope import snapshot_download
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model_dir = snapshot_download('xiaowangge/minicpm4-8b-gguf')
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```
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#### Git 下载
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```
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# Git模型下载
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git clone https://www.modelscope.cn/xiaowangge/minicpm4-8b-gguf.git
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```
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### 快速开始
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> 本地构建或下载预构建形式的 `llama.cpp` 文件，使用 `llama-cli` 推理。
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#### 源码构建 llama-cli
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```bash
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# 克隆 llama.cpp 源码
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git clone -b https://github.com/ggml-org/llama.cpp
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# 进入目录
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cd llama.cpp
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# 构建配置，开启 CUDA 加速，禁用 CURL
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cmake -B build -DGGML_CUDA=ON -DLLAMA_CURL=OFF
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# 多任务加速构建
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cmake --build build --config Release -j 10
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# 测试
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build/bin/llama-cli -h
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```
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#### llama-cli 推理
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```bash
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# GPU 加速
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build/bin/llama-cli -m ./minicpm4-8b-fp16.gguf -c 1024 -ngl 128 -n 512 -p "介绍下你自己"
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```
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#### ollama 推理
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> 如果不想进行复杂的 `llama.cpp `编译或配置，可使用 `ollama(version>=0.9.2)` 快速推理。
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```bash
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ollama run xiaowangge/minicpm4
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```
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1
configuration.json
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{"framework":"Pytorch","task":"text-generation"}
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3
minicpm4-8b-fp16.gguf
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minicpm4-8b-fp16.gguf
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version https://git-lfs.github.com/spec/v1
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size 16372735296
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3
minicpm4-8b-q4_K_M.gguf
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minicpm4-8b-q4_K_M.gguf
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version https://git-lfs.github.com/spec/v1
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size 4965526080
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3
minicpm4-8b-q8_0.gguf
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minicpm4-8b-q8_0.gguf
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version https://git-lfs.github.com/spec/v1
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size 8699309376
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