How to use from
llama.cpp
Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf HuanLin/ayaka:Q4_0_AKAYA
# Run inference directly in the terminal:
llama-cli -hf HuanLin/ayaka:Q4_0_AKAYA
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf HuanLin/ayaka:Q4_0_AKAYA
# Run inference directly in the terminal:
llama-cli -hf HuanLin/ayaka:Q4_0_AKAYA
Use pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf HuanLin/ayaka:Q4_0_AKAYA
# Run inference directly in the terminal:
./llama-cli -hf HuanLin/ayaka:Q4_0_AKAYA
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf HuanLin/ayaka:Q4_0_AKAYA
# Run inference directly in the terminal:
./build/bin/llama-cli -hf HuanLin/ayaka:Q4_0_AKAYA
Use Docker
docker model run hf.co/HuanLin/ayaka:Q4_0_AKAYA
Quick Links

神里绫华 LLM 模型

Train on RTX 3090x2

Based on Qwen2-7b-Instruct

Datasets are collected by @zzc想睡觉觉觉觉觉

使用方式

下载后

ollama create akaya -f ./Modelfile
ollama run akaya

其他

除了 Q4_0 量化以外,还提供了 Q8_0 量化的模型,请自己更改配置

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Model size
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Architecture
qwen2
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