Instructions to use ksharp8/maxnlp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ksharp8/maxnlp with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ksharp8/maxnlp", device_map="auto") - llama-cpp-python
How to use ksharp8/maxnlp with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="ksharp8/maxnlp", filename="unsloth.Q8_0.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use ksharp8/maxnlp 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 ksharp8/maxnlp:Q8_0 # Run inference directly in the terminal: llama cli -hf ksharp8/maxnlp:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ksharp8/maxnlp:Q8_0 # Run inference directly in the terminal: llama cli -hf ksharp8/maxnlp: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 ksharp8/maxnlp:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf ksharp8/maxnlp: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 ksharp8/maxnlp:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf ksharp8/maxnlp:Q8_0
Use Docker
docker model run hf.co/ksharp8/maxnlp:Q8_0
- LM Studio
- Jan
- Ollama
How to use ksharp8/maxnlp with Ollama:
ollama run hf.co/ksharp8/maxnlp:Q8_0
- Unsloth Studio
How to use ksharp8/maxnlp 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 ksharp8/maxnlp 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 ksharp8/maxnlp to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ksharp8/maxnlp to start chatting
- Atomic Chat new
- Docker Model Runner
How to use ksharp8/maxnlp with Docker Model Runner:
docker model run hf.co/ksharp8/maxnlp:Q8_0
- Lemonade
How to use ksharp8/maxnlp with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ksharp8/maxnlp:Q8_0
Run and chat with the model
lemonade run user.maxnlp-Q8_0
List all available models
lemonade list
| -- phpMyAdmin SQL Dump | |
| -- version 4.8.5 | |
| -- https://www.phpmyadmin.net/ | |
| -- | |
| -- 主机: localhost | |
| -- 生成日期: 2023-05-03 17:38:00 | |
| -- 服务器版本: 5.7.26 | |
| -- PHP 版本: 7.3.4 | |
| SET SQL_MODE = "NO_AUTO_VALUE_ON_ZERO"; | |
| SET AUTOCOMMIT = 0; | |
| START TRANSACTION; | |
| SET time_zone = "+00:00"; | |
| /*!40101 SET @OLD_CHARACTER_SET_CLIENT=@@CHARACTER_SET_CLIENT */; | |
| /*!40101 SET @OLD_CHARACTER_SET_RESULTS=@@CHARACTER_SET_RESULTS */; | |
| /*!40101 SET @OLD_COLLATION_CONNECTION=@@COLLATION_CONNECTION */; | |
| /*!40101 SET NAMES utf8mb4 */; | |
| -- | |
| -- 数据库: `nlp` | |
| -- | |
| -- -------------------------------------------------------- | |
| -- | |
| -- 表的结构 `query` | |
| -- | |
| CREATE TABLE `query` ( | |
| `id` tinyint(4) NOT NULL, | |
| `q1` text COLLATE utf8_unicode_ci NOT NULL, | |
| `q2` text COLLATE utf8_unicode_ci NOT NULL, | |
| `q3` text COLLATE utf8_unicode_ci NOT NULL, | |
| `a1` text COLLATE utf8_unicode_ci NOT NULL, | |
| `a2` text COLLATE utf8_unicode_ci NOT NULL, | |
| `a3` text COLLATE utf8_unicode_ci NOT NULL, | |
| `update_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP, | |
| `is_del` tinyint(1) NOT NULL | |
| ) ENGINE=MyISAM DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci; | |
| -- | |
| -- 转存表中的数据 `query` | |
| -- | |
| INSERT INTO `query` (`id`, `q1`, `q2`, `q3`, `a1`, `a2`, `a3`, `update_time`, `is_del`) VALUES | |
| (1, '你好吗', '你好', '好吗', '我很好', '我一般', '我不好', '2023-05-03 07:57:35', 0), | |
| (2, '再见', '再会', '拜拜', '再见', '再会', '拜拜', '2023-05-03 07:58:16', 0), | |
| (3, '在吗', '在', '在不在', '不在', '在', '在的', '2023-05-03 09:03:52', 0), | |
| (5, '你是谁', '是谁', '你是', '我是宅晓萌', '宅晓萌', '宅萌', '2023-05-03 09:05:53', 0), | |
| (6, '你在哪儿', '在哪儿', '哪里', '上海', '在上海', '上海地界', '2023-05-03 09:06:41', 0), | |
| (7, '你有钱吗', '有钱吗', '有没有钱', '有钱', '没钱', '有点钱', '2023-05-03 09:07:18', 0), | |
| (8, '你在干嘛', '干什么', '干嘛', '在干你', '在干杯', '在干咳', '2023-05-03 09:08:01', 0), | |
| (9, '你好看吗', '好看吗', '漂亮吗', '你说呢', '我不说', '你猜', '2023-05-03 09:09:27', 0), | |
| (10, '你住哪里', '住哪里', '住哪', '住家里', '住公司', '住天桥', '2023-05-03 09:11:39', 0), | |
| (11, '你吃什么', '吃什么', '吃吗', '吃好吃的', '随便吃', '想吃什么吃什么', '2023-05-03 09:11:39', 0), | |
| (12, '喝什么', '喝啥', '喝吗', '喝酒', '喝茶', '喝饮料', '2023-05-03 09:21:01', 0), | |
| (13, '你吐吗', '吐吗', '会吐', '吐什么', '吐你吗', '吐口水?', '2023-05-03 09:21:01', 0), | |
| (14, '你做什么的', '做什么', '什么工作', '艺术家', '搞艺术的', '有点艺术细胞', '2023-05-03 09:22:41', 0), | |
| (15, '你会剪辑吗', '会剪辑吗', '能剪辑吗', '会剪辑', '不会吧', '剪什么', '2023-05-03 09:22:41', 0), | |
| (16, '你会编程吗', '会编程吗', '能编程吗', '会十种编程语言', '只会编批处理', '只会bash命令', '2023-05-03 09:24:33', 0), | |
| (17, '你会设计吗', '会设计吗', '能设计吗', '设计了个马', '外号徐悲鸿', '张大千是我祖先', '2023-05-03 09:24:33', 0), | |
| (18, '你哪里毕业', '什么学校', '什么大学', '华冈艺校', '上戏毕业的', '家里蹲大学', '2023-05-03 09:28:10', 0), | |
| (19, '你有车吗', '有车吗', '车呢', '11路电车', '特斯拉model3', '凯迪拉克缩短版', '2023-05-03 09:30:20', 0), | |
| (20, '你有房吗', '有房吗', '有房', '租了套总统套间', '住在小别墅里', '住在花园洋房', '2023-05-03 09:30:20', 0), | |
| (21, '你相亲吗', '相亲吗', '搞对象吗', '我开相亲网站', '我牵红线的', '亲相我', '2023-05-03 09:32:11', 0), | |
| (22, '你工作几年', '工作几年', '社会阅历', '工作了一辈子', '凑够退休年龄', '职场新人', '2023-05-03 09:32:11', 0), | |
| (23, '你是神吗', '你是神', '是神吗', '我信佛', '我信耶稣', '我信真主安拉', '2023-05-03 09:35:30', 0), | |
| (24, '去过太空吗', '去太空吗', '上太空', '要么你太空了', '现在技术不发达', '现在可能不安全', '2023-05-03 09:35:30', 0), | |
| (25, '有文化吗', '读书吗', '上大学吗', '我博士结业', '我读四个大学', '我看几千本书', '2023-05-03 09:37:23', 0); | |
| -- | |
| -- 转储表的索引 | |
| -- | |
| -- | |
| -- 表的索引 `query` | |
| -- | |
| ALTER TABLE `query` | |
| ADD PRIMARY KEY (`id`); | |
| -- | |
| -- 在导出的表使用AUTO_INCREMENT | |
| -- | |
| -- | |
| -- 使用表AUTO_INCREMENT `query` | |
| -- | |
| ALTER TABLE `query` | |
| MODIFY `id` tinyint(4) NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=26; | |
| COMMIT; | |
| /*!40101 SET CHARACTER_SET_CLIENT=@OLD_CHARACTER_SET_CLIENT */; | |
| /*!40101 SET CHARACTER_SET_RESULTS=@OLD_CHARACTER_SET_RESULTS */; | |
| /*!40101 SET COLLATION_CONNECTION=@OLD_COLLATION_CONNECTION */; | |