Instructions to use MoYoYoTech/Translator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use MoYoYoTech/Translator 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 MoYoYoTech/Translator:Q5_0 # Run inference directly in the terminal: llama cli -hf MoYoYoTech/Translator:Q5_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf MoYoYoTech/Translator:Q5_0 # Run inference directly in the terminal: llama cli -hf MoYoYoTech/Translator:Q5_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 MoYoYoTech/Translator:Q5_0 # Run inference directly in the terminal: ./llama-cli -hf MoYoYoTech/Translator:Q5_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 MoYoYoTech/Translator:Q5_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf MoYoYoTech/Translator:Q5_0
Use Docker
docker model run hf.co/MoYoYoTech/Translator:Q5_0
- LM Studio
- Jan
- Ollama
How to use MoYoYoTech/Translator with Ollama:
ollama run hf.co/MoYoYoTech/Translator:Q5_0
- Unsloth Studio
How to use MoYoYoTech/Translator with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for MoYoYoTech/Translator to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for MoYoYoTech/Translator to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for MoYoYoTech/Translator to start chatting
- Pi
How to use MoYoYoTech/Translator with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf MoYoYoTech/Translator:Q5_0
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "MoYoYoTech/Translator:Q5_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use MoYoYoTech/Translator with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf MoYoYoTech/Translator:Q5_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 MoYoYoTech/Translator:Q5_0
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use MoYoYoTech/Translator with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf MoYoYoTech/Translator:Q5_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 "MoYoYoTech/Translator:Q5_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"
- Docker Model Runner
How to use MoYoYoTech/Translator with Docker Model Runner:
docker model run hf.co/MoYoYoTech/Translator:Q5_0
- Lemonade
How to use MoYoYoTech/Translator with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull MoYoYoTech/Translator:Q5_0
Run and chat with the model
lemonade run user.Translator-Q5_0
List all available models
lemonade list
File size: 10,548 Bytes
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import { ref, computed } from 'vue';
// 定义会话中单个节点的结构 (如果比纯文本更复杂)
export interface SessionNode {
id: string; // 或者其他唯一标识符
text: string;
translatedText?: string; // 可选的翻译文本
timestamp: number; // 时间戳
// 可以添加其他元数据,如语言、说话人等
}
// 定义存储在 Pinia 和用于 Modal 列表的会话摘要结构
export interface SessionSummary {
startTime: number; // 作为唯一 ID 和排序依据
title: string; // 第一句话的前10个字
outline: string[]; // 前两行内容
nodeCount: number; // 会话中的节点总数
}
const LOCAL_STORAGE_SESSION_PREFIX = 'rt_session_'; // 本地存储键前缀
export const useSessionStore = defineStore('session', () => {
// --- State ---
// 会话摘要列表,将由 pinia-plugin-persistedstate 自动持久化
const sessionSummaries = ref<SessionSummary[]>([]);
// 当前活动会话的节点 (不持久化)
const currentSessionNodes = ref<SessionNode[]>([]);
// 当前活动会话的开始时间 (不持久化)
const currentSessionStartTime = ref<number | null>(null);
// 标记会话是否正在进行中 (不持久化)
const isSessionActive = ref(false);
// --- Getters ---
// 按开始时间降序排列的会话摘要
const sortedSessionSummaries = computed(() => {
// 创建副本进行排序,避免直接修改响应式 ref
return [...sessionSummaries.value].sort((a, b) => b.startTime - a.startTime);
});
// --- Actions ---
/**
* 开始一个新的会话
*/
function startSession() {
if (isSessionActive.value) {
console.warn("尝试在已有活动会话时开始新会话。");
// 可以选择结束旧会话或直接返回
// endSession(); // 如果需要自动结束旧会话
return;
}
currentSessionStartTime.value = Date.now();
currentSessionNodes.value = [];
isSessionActive.value = true;
console.log(`新会话开始于: ${new Date(currentSessionStartTime.value).toLocaleString()}`);
}
/**
* 向当前活动会话添加一个节点
* @param node - 要添加的会话节点
*/
function addNode(node: SessionNode) {
if (!isSessionActive.value || !currentSessionStartTime.value) {
console.warn("没有活动的会话来添加节点。");
return;
}
currentSessionNodes.value.push(node);
// 可选:如果需要更强的容错性,可以在这里进行增量保存到 localStorage
// saveCurrentSessionToLocalStorage();
}
/**
* 结束当前活动会话,保存完整内容到 localStorage,并更新摘要列表
*/
function endSession() {
if (!isSessionActive.value || !currentSessionStartTime.value) {
console.log("没有活动的会话可以结束。");
// 确保状态被重置
isSessionActive.value = false;
currentSessionStartTime.value = null;
currentSessionNodes.value = [];
return;
}
const startTime = currentSessionStartTime.value;
const nodes = [...currentSessionNodes.value]; // 创建副本
// 重置当前会话状态
isSessionActive.value = false;
currentSessionStartTime.value = null;
currentSessionNodes.value = [];
if (nodes.length === 0) {
console.log("会话结束,但没有节点需要保存。");
return;
}
// 1. 生成摘要信息
const title = nodes[0]?.text.substring(0, 10) || '无标题会话';
const n1 = nodes[0];
const outline = [
`${n1?.text.substring(0, 56)}...\n`,
`${n1?.translatedText?.substring(0, 56)}...\n`,
]
// `${n1?.text.substring(0, 56)}\n${'-'.repeat(60)}\n${n1.translatedText?.substring(0, 56)}\n`
const summary: SessionSummary = {
startTime,
title,
outline,
nodeCount: nodes.length,
};
// 2. 保存完整会话内容到 Local Storage
try {
const storageKey = `${LOCAL_STORAGE_SESSION_PREFIX}${startTime}`;
localStorage.setItem(storageKey, JSON.stringify(nodes));
console.log(`完整会话 ${startTime} 已保存到 localStorage.`);
// 3. 更新 Pinia 中的摘要列表
// 检查是否已存在相同 startTime 的摘要 (理论上不应发生,除非手动操作或错误)
const existingIndex = sessionSummaries.value.findIndex(s => s.startTime === startTime);
if (existingIndex === -1) {
sessionSummaries.value.push(summary);
} else {
console.warn(`会话摘要 ${startTime} 已存在,将进行覆盖。`);
sessionSummaries.value[existingIndex] = summary;
}
// pinia-plugin-persistedstate 会自动处理 sessionSummaries 的持久化
console.log(`会话 ${startTime} 结束并已处理。`);
} catch (error) {
console.error("保存会话到 localStorage 时出错:", error);
// 这里可以添加用户反馈,例如提示存储空间不足
// 也许需要决定是否回滚摘要列表的添加
}
}
/**
* 从 Local Storage 加载指定会话的完整内容
* @param startTime - 会话的开始时间戳 (作为 ID)
* @returns SessionNode[] | null - 会话节点数组或在未找到/出错时返回 null
*/
function loadSessionContent(startTime: number): SessionNode[] | null {
try {
const storageKey = `${LOCAL_STORAGE_SESSION_PREFIX}${startTime}`;
const storedData = localStorage.getItem(storageKey);
if (storedData) {
const nodes = JSON.parse(storedData) as SessionNode[];
console.log(`从 localStorage 加载了会话 ${startTime} 的内容 (${nodes.length} 个节点)`);
return nodes;
}
console.warn(`在 localStorage 中未找到键为 ${storageKey} 的会话数据。`);
return null;
} catch (error) {
console.error(`从 localStorage 加载会话 ${startTime} 时出错:`, error);
return null;
}
}
/**
* 删除指定的会话 (包括摘要和本地存储的完整内容)
* @param startTime - 要删除的会话的开始时间戳
*/
function deleteSession(startTime: number) {
try {
// 1. 从摘要列表中移除
const index = sessionSummaries.value.findIndex(s => s.startTime === startTime);
if (index > -1) {
sessionSummaries.value.splice(index, 1);
console.log(`会话摘要 ${startTime} 已从 Pinia store 中移除。`);
// pinia-plugin-persistedstate 会自动更新持久化的摘要列表
} else {
console.warn(`尝试删除一个不存在的会话摘要: ${startTime}`);
}
// 2. 从 Local Storage 中移除完整内容
const storageKey = `${LOCAL_STORAGE_SESSION_PREFIX}${startTime}`;
localStorage.removeItem(storageKey);
console.log(`会话 ${startTime} 的完整内容已从 localStorage 中移除。`);
} catch (error) {
console.error(`删除会话 ${startTime} 时出错:`, error);
}
}
// --- 返回 State, Getters, Actions ---
return {
// State
sessionSummaries, // 摘要列表 (将被持久化)
currentSessionNodes, // 当前活动会话的节点 (用于可能的实时显示)
currentSessionStartTime, // 当前活动会话的开始时间
isSessionActive, // 会话是否活动
// Getters
sortedSessionSummaries, // 排序后的摘要列表
// Actions
startSession,
addNode,
endSession,
loadSessionContent, // 用于下载按钮点击时加载数据
deleteSession,
};
}, {
// Pinia 持久化配置
persist: {
// 只持久化 sessionSummaries 状态
paths: ['sessionSummaries'],
// 默认使用 localStorage,如果需要可以指定
// storage: localStorage,
},
});
/**
* 辅助函数:触发浏览器下载会话数据
* @param startTime - 会话开始时间,用于文件名
* @param nodes - 要下载的会话节点数据
* @param format - 'json' 或 'txt' (默认为 'json')
*/
export function downloadSessionData(startTime: number, nodes: SessionNode[], format: 'json' | 'txt' = 'json') {
if (!nodes || nodes.length === 0) {
console.error("没有数据可供下载:", startTime);
alert("没有内容可以下载。"); // 给用户反馈
return;
}
try {
const dateStr = new Date(startTime).toISOString().split('T')[0]; // YYYY-MM-DD
let dataStr: string;
let mimeType: string;
let fileExtension: string;
if (format === 'txt') {
dataStr = nodes.map(n => `${new Date(n.timestamp).toLocaleTimeString()} - ${n.text}`).join('\n');
mimeType = 'text/plain;charset=utf-8;';
fileExtension = 'txt';
} else { // 默认为 json
dataStr = JSON.stringify(nodes, null, 2); // 美化 JSON 输出
mimeType = 'application/json;charset=utf-8;';
fileExtension = 'json';
}
const filename = `session_${dateStr}_${startTime}.${fileExtension}`;
const blob = new Blob([dataStr], { type: mimeType });
const link = document.createElement("a");
// 使用 createObjectURL 创建一个临时的 URL 指向 Blob 对象
const url = URL.createObjectURL(blob);
link.setAttribute("href", url);
link.setAttribute("download", filename);
link.style.visibility = 'hidden';
document.body.appendChild(link);
link.click(); // 模拟点击下载链接
// 清理:移除链接并释放 URL 对象
document.body.removeChild(link);
URL.revokeObjectURL(url);
console.log(`已触发下载会话 ${startTime} 为 ${filename}`);
} catch (error) {
console.error(`下载会话 ${startTime} 时出错:`, error);
alert("下载文件时发生错误。"); // 给用户反馈
}
}
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