Instructions to use startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF 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 startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF: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 startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF: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 startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF:Q8_0

Use Docker

docker model run hf.co/startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF:Q8_0

LM Studio
Jan
Ollama
How to use startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF with Ollama:
```
ollama run hf.co/startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF:Q8_0
```
Unsloth Desktop

How to use startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF: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": "startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF with Docker Model Runner:
```
docker model run hf.co/startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF:Q8_0
```

Lemonade

How to use startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF:Q8_0

Run and chat with the model

lemonade run user.StartLux-Decision-v1-27B-Q8_0-GGUF-Q8_0

List all available models

lemonade list

Hermes Agent

How to use startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF: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 startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF:Q8_0

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF: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 "startlux-models/StartLux-Decision-v1-27B-Q8_0-GGUF: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"

fix(gguf_server): fail-closed on null logprob / empty probs from llama-server

by civilizationabc - opened 7 days ago

base: refs/heads/main

←

from: refs/pr/3

Discussion Files changed

-1

civilizationabc

7 days ago

背景

2026-10-05 实证：StartLux-Decision-27B 在「双问并发（disclosed+supports）」时必然失败，
报 TypeError: must be real number, not NoneType @ gguf_server.py:63。

根因

上游 llama-server 在失败态返回 top_logprobs 带 logprob: null（或无 probs）。
_letter_logprobs 不区分该失败态，[got[t] ...] 中出现 None，_logits 的
torch.tensor(...) 裸崩。单问各自均 PASS，故不是内容/长度/语言/配额问题。

改动

_letter_logprobs：rows 为空 → 换更大 n_probs 重试；目标字母 logprob 为 null → 也视为失败重试。
_logits：末尾 fail-closed 汇总 null 数并抛结构化 RuntimeError（指向 llama-server.log / SD27B_DIAG）。

影响面

仅改失败处理，不改推理数值。补丁已 py_compile 通过。

验证

Space 侧已用等效手段（GGUFDecision workers=4→1 串行化）消除并发争用，双问行判定 SUCCESS。
本 PR 的守卫使错误可读性更佳，非恢复必需。

fix(gguf_server): fail-closed on null logprob / empty probs from llama-server645d0811

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