Spaces:
Running
Running
File size: 5,562 Bytes
0a28e1c 2935f03 0a28e1c f8410ae 0a28e1c 01772d1 6cd6f81 ccf3203 0a28e1c 5073684 01772d1 6656923 b143197 6656923 b143197 6656923 b143197 6656923 b143197 6656923 b143197 6656923 b143197 6656923 b143197 6656923 b143197 6656923 b143197 6656923 b143197 6656923 b143197 6656923 01772d1 5073684 01772d1 0a28e1c 2935f03 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 |
<!doctype html public "-//W3C//DTD HTML 4.0 Transitional //EN">
<html>
<head>
<meta name="GENERATOR" content="mkd2html 2.2.7 GITHUB_CHECKBOX">
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<link rel="stylesheet"
type="text/css"
href="header.css" />
<title></title>
</head>
<body>
<h1>Seamless Integration of GNU operating system with Large Language Models: Enhancing Performance and Usability</h1>
<blockquote><p>Author: Jean Louis <bugs at gnu.support>, XMPP: <a href="xmpp:[email protected]">[email protected]</a><br/>
Last updated: Sun 23 Mar 2025 10:44:24 AM EAT</p></blockquote>
<p>This Hugging Face Space focuses on integrating GNU-like operating
systems with Large Language Models (LLMs). This development marks an
important step forward for free software, as outlined in the <a href="https://www.gnu.org/philosophy/free-sw.html">GNU
philosophy</a>, by enabling
users to interact more efficiently and effectively.</p>
<p>The primary goal of this brief project is to enhance how you interact
with computers initially and subsequently improve interactions between
people as a secondary objective.</p>
<p>Utilize these empowerment tools to deepen mutual comprehension with
others, strengthen both personal and professional connections, boost
promotional efforts for better market reach, increase sales
opportunities overall—ultimately aiding in the enhancement of various
aspects of your life.</p>
<h2>First Stage Goal: Enable Speech Interaction With Computer</h2>
<p>🚀 In the first stage of our adventure together, we aim to enable
speech interaction between you and your machine. Imagine effortlessly
asking questions or giving commands just by speaking!</p>
<p>We’ll explore tools like voice recognition software that will listen
intently as if it’s hanging on every word (because let’s be honest,
who doesn’t love a good listener?). By the end of this stage, you’ll
feel empowered to chat away and make your computer truly understand
what makes <em>you</em> tick. Let’s dive in together! 🎤💻✨</p>
<h3>Install required software</h3>
<h4>Prepare Python environment to download Hugging Face models</h4>
<p>This guide will help you install the necessary Hugging Face packages
and tools to download and use models from the Hugging Face Hub.</p>
<hr />
<h5>1. Install <code>transformers</code> Package</h5>
<p>The <code>transformers</code> package is used to load and use Hugging Face models in Python.</p>
<h6>Installation</h6>
<p>Run the following command in your terminal or command prompt:</p>
<p><code>bash
pip install transformers
</code></p>
<h6>Verify Installation</h6>
<p>To confirm the installation was successful, run:</p>
<p><code>bash
python -c "from transformers import pipeline; print('Installation successful!')"
</code></p>
<hr />
<h5>2. Install <code>huggingface_hub</code> Package</h5>
<p>The <code>huggingface_hub</code> package provides the <code>huggingface-cli</code> tool for interacting with the Hugging Face Hub (e.g., downloading models, uploading files, etc.).</p>
<h6>Installation</h6>
<p>Run the following command:</p>
<p><code>bash
pip install huggingface_hub
</code></p>
<h6>Verify Installation</h6>
<p>After installation, check if the <code>huggingface-cli</code> is available:</p>
<p><code>bash
huggingface-cli --help
</code></p>
<hr />
<h5>3. Using <code>huggingface-cli</code></h5>
<p>The <code>huggingface-cli</code> tool allows you to interact with the Hugging Face Hub directly from the command line.</p>
<h6>Common Commands</h6>
<h6>Log in to Hugging Face</h6>
<p>To log in to your Hugging Face account:</p>
<p><code>bash
huggingface-cli login
</code></p>
<h6>Download a Model</h6>
<p>To download a model (e.g., <code>gpt2</code>):</p>
<p><code>bash
huggingface-cli download gpt2
</code></p>
<h6>List Available Commands</h6>
<p>To see all available commands and options:</p>
<p><code>bash
huggingface-cli --help
</code></p>
<hr />
<h5>4. Example: Download and Use a Model</h5>
<p>Here’s an example of downloading and using a model in Python:</p>
<pre>
from transformers import pipeline
# Download and load a model
generator = pipeline("text-generation", model="gpt2")
# Generate text
output = generator("Hello, how are you?", max_length=50)
print(output)
</pre>
<hr />
<h5>5. Summary of Commands</h5>
<table>
<thead>
<tr>
<th> Command </th>
<th> Description </th>
</tr>
</thead>
<tbody>
<tr>
<td> <code>pip install transformers</code> </td>
<td> Install the <code>transformers</code> package. </td>
</tr>
<tr>
<td> <code>pip install huggingface_hub</code> </td>
<td> Install the <code>huggingface_hub</code> package. </td>
</tr>
<tr>
<td> <code>huggingface-cli --help</code> </td>
<td> List all available <code>huggingface-cli</code> commands. </td>
</tr>
<tr>
<td> <code>huggingface-cli login</code> </td>
<td> Log in to your Hugging Face account. </td>
</tr>
<tr>
<td> <code>huggingface-cli download gpt2</code> </td>
<td> Download the <code>gpt2</code> model. </td>
</tr>
</tbody>
</table>
<hr />
<p>Now you’re ready to use Hugging Face models and tools in Python! 🚀</p>
<h4>Install NVIDIA Canary-1B-Flash fully free software Large Language Model (LLM) for speech recognition</h4>
<h4>Run NVIDIA Canary-1B-Flash as server</h4>
<h4>Prepare Shell scripts</h4>
<h4>Configure mouse for seemless speech recognition</h4>
</body>
</html>
|