Instructions to use gasschina/Spark-X2.5-4B-build-cpp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use gasschina/Spark-X2.5-4B-build-cpp with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf gasschina/Spark-X2.5-4B-build-cpp:Q8_0
# Run inference directly in the terminal:
llama cli -hf gasschina/Spark-X2.5-4B-build-cpp:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf gasschina/Spark-X2.5-4B-build-cpp:Q8_0
# Run inference directly in the terminal:
llama cli -hf gasschina/Spark-X2.5-4B-build-cpp:Q8_0

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 gasschina/Spark-X2.5-4B-build-cpp:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf gasschina/Spark-X2.5-4B-build-cpp:Q8_0

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 gasschina/Spark-X2.5-4B-build-cpp:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf gasschina/Spark-X2.5-4B-build-cpp:Q8_0

Use Docker

docker model run hf.co/gasschina/Spark-X2.5-4B-build-cpp:Q8_0

LM Studio
Jan
Ollama
How to use gasschina/Spark-X2.5-4B-build-cpp with Ollama:
```
ollama run hf.co/gasschina/Spark-X2.5-4B-build-cpp:Q8_0
```
Unsloth Desktop

How to use gasschina/Spark-X2.5-4B-build-cpp with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf gasschina/Spark-X2.5-4B-build-cpp:Q8_0

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "gasschina/Spark-X2.5-4B-build-cpp:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use gasschina/Spark-X2.5-4B-build-cpp with Docker Model Runner:
```
docker model run hf.co/gasschina/Spark-X2.5-4B-build-cpp:Q8_0
```

Lemonade

How to use gasschina/Spark-X2.5-4B-build-cpp with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull gasschina/Spark-X2.5-4B-build-cpp:Q8_0

Run and chat with the model

lemonade run user.Spark-X2.5-4B-build-cpp-Q8_0

List all available models

lemonade list

Hermes Agent

How to use gasschina/Spark-X2.5-4B-build-cpp with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf gasschina/Spark-X2.5-4B-build-cpp:Q8_0

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default gasschina/Spark-X2.5-4B-build-cpp:Q8_0

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use gasschina/Spark-X2.5-4B-build-cpp with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf gasschina/Spark-X2.5-4B-build-cpp:Q8_0

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "gasschina/Spark-X2.5-4B-build-cpp:Q8_0" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

gasschina commited on 3 days ago

Commit

cd9d592

verified ·

1 Parent(s): e85191c

Upload scripts/spark_api.sh with huggingface_hub

Browse files

Files changed (1) hide show

scripts/spark_api.sh +3 -3

scripts/spark_api.sh CHANGED Viewed

@@ -14,7 +14,7 @@
 #   · 鉴权: 默认自动生成 API Key 存 Drive 并打印；API_KEY=off 可关闭
 #
 # 用法:
-#   bash spark_api.sh start     # 起服务（默认 Q4_K_M+1.7B草稿投机解码 @ CTX=262144, 思考默认关）
 #   关闭投机解码: SPEC_TYPE=none CTX=500000 bash spark_api.sh start
 #   开启思考模式: THINKING=on bash spark_api.sh start（⚠️ 非流式请求可能超网关 120s 超时→504）
 #   bash spark_api.sh stop
@@ -26,9 +26,9 @@ set -euo pipefail
 BASE_DIR="${BASE_DIR:-/content/drive/MyDrive/spark-t4}"
 MODEL_DIR="${MODEL_DIR:-/content/spark-t4-models}"
-QUANT="${QUANT:-Q4_K_M}"                   # 默认 4bit(提速+省显存); Q8_0 质量优先时显式指定
 CTX="${CTX:-262144}"                       # 256k 默认（配合默认投机解码）；关草稿后可设 524288/500000(需KVQ)
-PORT="${PORT:-8080}"
 NGL="${NGL:-999}"
 KVQ="${KVQ:-}"                             # KV cache 量化: q8_0 / q4_0，压显存换长上下文
 API_KEY="${API_KEY:-auto}"                 # auto=首次生成并存Drive; off=不鉴权

 #   · 鉴权: 默认自动生成 API Key 存 Drive 并打印；API_KEY=off 可关闭
 #
 # 用法:
+#   bash spark_api.sh start     # 起服务（默认 Q8_0+1.7B草稿投机解码 @ CTX=262144, 思考默认关）
 #   关闭投机解码: SPEC_TYPE=none CTX=500000 bash spark_api.sh start
 #   开启思考模式: THINKING=on bash spark_api.sh start（⚠️ 非流式请求可能超网关 120s 超时→504）
 #   bash spark_api.sh stop
 BASE_DIR="${BASE_DIR:-/content/drive/MyDrive/spark-t4}"
 MODEL_DIR="${MODEL_DIR:-/content/spark-t4-models}"
+QUANT="${QUANT:-Q8_0}"                     # 默认 Q8_0(质量最佳+草稿接受率0.89≈52tok/s); 4bit省显存: QUANT=Q4_K_M
 CTX="${CTX:-262144}"                       # 256k 默认（配合默认投机解码）；关草稿后可设 524288/500000(需KVQ)
+PORT="${PORT:-8100}"                       # 8100 默认(Colab 的 8080 被占用); 本机另跑时 PORT=8080 覆盖
 NGL="${NGL:-999}"
 KVQ="${KVQ:-}"                             # KV cache 量化: q8_0 / q4_0，压显存换长上下文
 API_KEY="${API_KEY:-auto}"                 # auto=首次生成并存Drive; off=不鉴权