Update README.md
Browse files
README.md
CHANGED
|
@@ -23,36 +23,52 @@ pipeline_tag: text-generation
|
|
| 23 |
--brown: #b08968;
|
| 24 |
--ink: #4a3728;
|
| 25 |
--muted: #8a6f52;
|
| 26 |
-
--
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 27 |
}
|
| 28 |
.bleyzos {
|
| 29 |
max-width: 960px;
|
| 30 |
margin: 0 auto;
|
| 31 |
display: flex;
|
| 32 |
flex-direction: column;
|
| 33 |
-
gap:
|
| 34 |
-
font-family: var(--font);
|
| 35 |
-
color: var(--ink);
|
| 36 |
}
|
| 37 |
.bleyzos-header {
|
| 38 |
display: flex;
|
| 39 |
align-items: center;
|
| 40 |
-
gap:
|
| 41 |
padding: 16px 20px;
|
| 42 |
-
border-radius:
|
| 43 |
background: linear-gradient(135deg, var(--bg), var(--bg-2));
|
| 44 |
border: 1px solid var(--line);
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 45 |
}
|
| 46 |
.bleyzos-header img {
|
|
|
|
| 47 |
width: 84px;
|
| 48 |
height: 84px;
|
| 49 |
border-radius: 14px;
|
| 50 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
| 51 |
}
|
| 52 |
.bleyzos-header h1 {
|
| 53 |
margin: 0;
|
| 54 |
font-size: clamp(1.6em, 4vw, 2em);
|
| 55 |
font-weight: 800;
|
|
|
|
| 56 |
background: linear-gradient(90deg, var(--brown), var(--sand), var(--gold));
|
| 57 |
-webkit-background-clip: text;
|
| 58 |
background-clip: text;
|
|
@@ -60,13 +76,21 @@ pipeline_tag: text-generation
|
|
| 60 |
}
|
| 61 |
.bleyzos-header p {
|
| 62 |
margin: 4px 0 0;
|
|
|
|
| 63 |
color: var(--muted);
|
|
|
|
| 64 |
}
|
| 65 |
.bleyzos-nav {
|
| 66 |
display: flex;
|
| 67 |
justify-content: center;
|
| 68 |
align-items: center;
|
| 69 |
gap: 12px;
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 70 |
color: var(--muted);
|
| 71 |
}
|
| 72 |
.bleyzos-nav a {
|
|
@@ -76,6 +100,12 @@ pipeline_tag: text-generation
|
|
| 76 |
border-radius: 999px;
|
| 77 |
background: linear-gradient(90deg, var(--sand), var(--gold));
|
| 78 |
color: var(--ink) !important;
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 79 |
}
|
| 80 |
.bleyzos-divider {
|
| 81 |
height: 2px;
|
|
@@ -86,8 +116,14 @@ pipeline_tag: text-generation
|
|
| 86 |
.bleyzos-card {
|
| 87 |
background: linear-gradient(135deg, var(--bg), var(--bg-2));
|
| 88 |
border: 1px solid var(--line);
|
| 89 |
-
border-radius:
|
| 90 |
-
padding:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 91 |
}
|
| 92 |
.bleyzos-card table {
|
| 93 |
width: 100%;
|
|
@@ -99,22 +135,44 @@ pipeline_tag: text-generation
|
|
| 99 |
color: var(--muted);
|
| 100 |
font-size: 0.85em;
|
| 101 |
text-transform: uppercase;
|
|
|
|
| 102 |
border-bottom: 1px solid var(--line);
|
| 103 |
}
|
| 104 |
.bleyzos-card td {
|
| 105 |
padding: 8px 10px;
|
| 106 |
border-bottom: 1px dashed var(--line);
|
|
|
|
| 107 |
}
|
| 108 |
.bleyzos-card tbody tr:last-child td {
|
| 109 |
border-bottom: none;
|
| 110 |
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 111 |
.bleyzos-footer {
|
| 112 |
text-align: center;
|
|
|
|
| 113 |
color: var(--muted);
|
| 114 |
-
padding:
|
| 115 |
-
border-radius:
|
| 116 |
background: linear-gradient(135deg, var(--bg), var(--bg-2));
|
| 117 |
border: 1px solid var(--line);
|
|
|
|
| 118 |
line-height: 1.7;
|
| 119 |
}
|
| 120 |
.bleyzos-footer a {
|
|
@@ -122,15 +180,20 @@ pipeline_tag: text-generation
|
|
| 122 |
text-decoration: none;
|
| 123 |
font-weight: 600;
|
| 124 |
}
|
|
|
|
|
|
|
|
|
|
| 125 |
</style>
|
| 126 |
|
| 127 |
<main class="bleyzos">
|
| 128 |
|
| 129 |
<header class="bleyzos-header">
|
| 130 |
-
<
|
| 131 |
-
<
|
| 132 |
-
|
| 133 |
-
|
|
|
|
|
|
|
| 134 |
<div>
|
| 135 |
<h1>Bleyzos</h1>
|
| 136 |
<p>Сообщество Bleyzos AI Center</p>
|
|
@@ -138,25 +201,25 @@ pipeline_tag: text-generation
|
|
| 138 |
</header>
|
| 139 |
|
| 140 |
<nav class="bleyzos-nav">
|
| 141 |
-
<
|
| 142 |
<a href="https://t.me/bleyzos" target="_blank" rel="noopener">Telegram</a>
|
| 143 |
</nav>
|
| 144 |
|
| 145 |
<hr class="bleyzos-divider">
|
| 146 |
|
| 147 |
-
<section>
|
| 148 |
-
<h2>Bleyzos Coder</h2>
|
| 149 |
<p><strong>Bleyzos Coder</strong> — открытая языковая модель на архитектуре Mixture-of-Experts (MoE) с <strong>1,02 трлн общих параметров</strong> и <strong>42 млрд активных параметров</strong>. Создана на основе форка MiMo-V2.5-Pro и дообучена для программирования, кибербезопасности и агентных сценариев. Поддерживает контекст до <strong>1 млн токенов</strong>.</p>
|
| 150 |
</section>
|
| 151 |
|
| 152 |
<hr class="bleyzos-divider">
|
| 153 |
|
| 154 |
-
<section>
|
| 155 |
-
<h2>Детали модели</h2>
|
| 156 |
<article class="bleyzos-card">
|
| 157 |
<table>
|
| 158 |
<thead>
|
| 159 |
-
<tr><th>Параметр</th><th>Значение</th></tr>
|
| 160 |
</thead>
|
| 161 |
<tbody>
|
| 162 |
<tr><td>Разработчик</td><td>Bleyzos AI (https://bleyzos.ru)</td></tr>
|
|
@@ -172,9 +235,9 @@ pipeline_tag: text-generation
|
|
| 172 |
|
| 173 |
<hr class="bleyzos-divider">
|
| 174 |
|
| 175 |
-
<section>
|
| 176 |
-
<h2>Ключевые особенности</h2>
|
| 177 |
-
<ul>
|
| 178 |
<li><strong>Гибридное внимание</strong> — Sliding Window Attention + Global Attention (6:1), снижает KV-cache ~в 7 раз.</li>
|
| 179 |
<li><strong>Multi-Token Prediction</strong> — 3 слоя MTP для ускорения вывода в 3 раза.</li>
|
| 180 |
<li><strong>Длинный контекст</strong> — до 1M токенов, можно подавать целые кодовые базы.</li>
|
|
@@ -185,8 +248,8 @@ pipeline_tag: text-generation
|
|
| 185 |
|
| 186 |
<hr class="bleyzos-divider">
|
| 187 |
|
| 188 |
-
<section>
|
| 189 |
-
<h2>Использование</h2>
|
| 190 |
<h3>Hugging Face Inference API</h3>
|
| 191 |
<pre><code class="language-python">from huggingface_hub import InferenceClient
|
| 192 |
|
|
|
|
| 23 |
--brown: #b08968;
|
| 24 |
--ink: #4a3728;
|
| 25 |
--muted: #8a6f52;
|
| 26 |
+
--radius: 16px;
|
| 27 |
+
--shadow-sm: 0 4px 14px rgba(176, 137, 104, 0.12);
|
| 28 |
+
--shadow-lg: 0 10px 26px rgba(176, 137, 104, 0.22);
|
| 29 |
+
--font: system-ui, -apple-system, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, sans-serif;
|
| 30 |
+
}
|
| 31 |
+
body {
|
| 32 |
+
font-family: var(--font);
|
| 33 |
+
color: var(--ink);
|
| 34 |
}
|
| 35 |
.bleyzos {
|
| 36 |
max-width: 960px;
|
| 37 |
margin: 0 auto;
|
| 38 |
display: flex;
|
| 39 |
flex-direction: column;
|
| 40 |
+
gap: 24px;
|
|
|
|
|
|
|
| 41 |
}
|
| 42 |
.bleyzos-header {
|
| 43 |
display: flex;
|
| 44 |
align-items: center;
|
| 45 |
+
gap: clamp(14px, 3vw, 22px);
|
| 46 |
padding: 16px 20px;
|
| 47 |
+
border-radius: var(--radius);
|
| 48 |
background: linear-gradient(135deg, var(--bg), var(--bg-2));
|
| 49 |
border: 1px solid var(--line);
|
| 50 |
+
box-shadow: var(--shadow-sm);
|
| 51 |
+
}
|
| 52 |
+
.bleyzos-header figure {
|
| 53 |
+
margin: 0;
|
| 54 |
+
flex-shrink: 0;
|
| 55 |
}
|
| 56 |
.bleyzos-header img {
|
| 57 |
+
display: block;
|
| 58 |
width: 84px;
|
| 59 |
height: 84px;
|
| 60 |
border-radius: 14px;
|
| 61 |
+
box-shadow: 0 0 18px rgba(212, 163, 115, 0.35);
|
| 62 |
+
transition: transform 0.3s ease;
|
| 63 |
+
}
|
| 64 |
+
.bleyzos-header img:hover {
|
| 65 |
+
transform: scale(1.06) rotate(-2deg);
|
| 66 |
}
|
| 67 |
.bleyzos-header h1 {
|
| 68 |
margin: 0;
|
| 69 |
font-size: clamp(1.6em, 4vw, 2em);
|
| 70 |
font-weight: 800;
|
| 71 |
+
letter-spacing: 1px;
|
| 72 |
background: linear-gradient(90deg, var(--brown), var(--sand), var(--gold));
|
| 73 |
-webkit-background-clip: text;
|
| 74 |
background-clip: text;
|
|
|
|
| 76 |
}
|
| 77 |
.bleyzos-header p {
|
| 78 |
margin: 4px 0 0;
|
| 79 |
+
font-size: 1.05em;
|
| 80 |
color: var(--muted);
|
| 81 |
+
opacity: 0.9;
|
| 82 |
}
|
| 83 |
.bleyzos-nav {
|
| 84 |
display: flex;
|
| 85 |
justify-content: center;
|
| 86 |
align-items: center;
|
| 87 |
gap: 12px;
|
| 88 |
+
flex-wrap: wrap;
|
| 89 |
+
text-align: center;
|
| 90 |
+
}
|
| 91 |
+
.bleyzos-nav strong {
|
| 92 |
+
font-size: 1.05em;
|
| 93 |
+
letter-spacing: 2px;
|
| 94 |
color: var(--muted);
|
| 95 |
}
|
| 96 |
.bleyzos-nav a {
|
|
|
|
| 100 |
border-radius: 999px;
|
| 101 |
background: linear-gradient(90deg, var(--sand), var(--gold));
|
| 102 |
color: var(--ink) !important;
|
| 103 |
+
box-shadow: 0 3px 10px rgba(212, 163, 115, 0.35);
|
| 104 |
+
transition: transform 0.25s ease, box-shadow 0.25s ease;
|
| 105 |
+
}
|
| 106 |
+
.bleyzos-nav a:hover {
|
| 107 |
+
transform: translateY(-2px) scale(1.04);
|
| 108 |
+
box-shadow: 0 7px 20px rgba(212, 163, 115, 0.5);
|
| 109 |
}
|
| 110 |
.bleyzos-divider {
|
| 111 |
height: 2px;
|
|
|
|
| 116 |
.bleyzos-card {
|
| 117 |
background: linear-gradient(135deg, var(--bg), var(--bg-2));
|
| 118 |
border: 1px solid var(--line);
|
| 119 |
+
border-radius: var(--radius);
|
| 120 |
+
padding: 20px 24px;
|
| 121 |
+
box-shadow: var(--shadow-sm);
|
| 122 |
+
transition: transform 0.3s ease, box-shadow 0.3s ease;
|
| 123 |
+
}
|
| 124 |
+
.bleyzos-card:hover {
|
| 125 |
+
transform: translateY(-3px);
|
| 126 |
+
box-shadow: var(--shadow-lg);
|
| 127 |
}
|
| 128 |
.bleyzos-card table {
|
| 129 |
width: 100%;
|
|
|
|
| 135 |
color: var(--muted);
|
| 136 |
font-size: 0.85em;
|
| 137 |
text-transform: uppercase;
|
| 138 |
+
letter-spacing: 1px;
|
| 139 |
border-bottom: 1px solid var(--line);
|
| 140 |
}
|
| 141 |
.bleyzos-card td {
|
| 142 |
padding: 8px 10px;
|
| 143 |
border-bottom: 1px dashed var(--line);
|
| 144 |
+
color: var(--ink);
|
| 145 |
}
|
| 146 |
.bleyzos-card tbody tr:last-child td {
|
| 147 |
border-bottom: none;
|
| 148 |
}
|
| 149 |
+
.bleyzos-features {
|
| 150 |
+
list-style: none;
|
| 151 |
+
padding: 0;
|
| 152 |
+
margin: 0;
|
| 153 |
+
display: grid;
|
| 154 |
+
gap: 10px;
|
| 155 |
+
}
|
| 156 |
+
.bleyzos-features li {
|
| 157 |
+
padding: 12px 16px;
|
| 158 |
+
border-radius: 12px;
|
| 159 |
+
background: linear-gradient(135deg, var(--bg), var(--bg-2));
|
| 160 |
+
border: 1px solid var(--line);
|
| 161 |
+
transition: transform 0.25s ease, box-shadow 0.25s ease;
|
| 162 |
+
}
|
| 163 |
+
.bleyzos-features li:hover {
|
| 164 |
+
transform: translateX(4px);
|
| 165 |
+
box-shadow: var(--shadow-sm);
|
| 166 |
+
}
|
| 167 |
.bleyzos-footer {
|
| 168 |
text-align: center;
|
| 169 |
+
font-size: 0.92em;
|
| 170 |
color: var(--muted);
|
| 171 |
+
padding: 20px 16px;
|
| 172 |
+
border-radius: var(--radius);
|
| 173 |
background: linear-gradient(135deg, var(--bg), var(--bg-2));
|
| 174 |
border: 1px solid var(--line);
|
| 175 |
+
box-shadow: var(--shadow-sm);
|
| 176 |
line-height: 1.7;
|
| 177 |
}
|
| 178 |
.bleyzos-footer a {
|
|
|
|
| 180 |
text-decoration: none;
|
| 181 |
font-weight: 600;
|
| 182 |
}
|
| 183 |
+
.bleyzos-footer a:hover {
|
| 184 |
+
text-decoration: underline;
|
| 185 |
+
}
|
| 186 |
</style>
|
| 187 |
|
| 188 |
<main class="bleyzos">
|
| 189 |
|
| 190 |
<header class="bleyzos-header">
|
| 191 |
+
<figure>
|
| 192 |
+
<picture>
|
| 193 |
+
<source srcset="https://cdn.bleyzos.ru/logo.png" media="(prefers-color-scheme: dark)">
|
| 194 |
+
<img src="https://cdn.bleyzos.ru/logo.png" alt="Логотип Bleyzos Coder">
|
| 195 |
+
</picture>
|
| 196 |
+
</figure>
|
| 197 |
<div>
|
| 198 |
<h1>Bleyzos</h1>
|
| 199 |
<p>Сообщество Bleyzos AI Center</p>
|
|
|
|
| 201 |
</header>
|
| 202 |
|
| 203 |
<nav class="bleyzos-nav">
|
| 204 |
+
<strong>СООБЩЕСТВО</strong>
|
| 205 |
<a href="https://t.me/bleyzos" target="_blank" rel="noopener">Telegram</a>
|
| 206 |
</nav>
|
| 207 |
|
| 208 |
<hr class="bleyzos-divider">
|
| 209 |
|
| 210 |
+
<section aria-labelledby="about">
|
| 211 |
+
<h2 id="about">Bleyzos Coder</h2>
|
| 212 |
<p><strong>Bleyzos Coder</strong> — открытая языковая модель на архитектуре Mixture-of-Experts (MoE) с <strong>1,02 трлн общих параметров</strong> и <strong>42 млрд активных параметров</strong>. Создана на основе форка MiMo-V2.5-Pro и дообучена для программирования, кибербезопасности и агентных сценариев. Поддерживает контекст до <strong>1 млн токенов</strong>.</p>
|
| 213 |
</section>
|
| 214 |
|
| 215 |
<hr class="bleyzos-divider">
|
| 216 |
|
| 217 |
+
<section aria-labelledby="details">
|
| 218 |
+
<h2 id="details">Детали модели</h2>
|
| 219 |
<article class="bleyzos-card">
|
| 220 |
<table>
|
| 221 |
<thead>
|
| 222 |
+
<tr><th scope="col">Параметр</th><th scope="col">Значение</th></tr>
|
| 223 |
</thead>
|
| 224 |
<tbody>
|
| 225 |
<tr><td>Разработчик</td><td>Bleyzos AI (https://bleyzos.ru)</td></tr>
|
|
|
|
| 235 |
|
| 236 |
<hr class="bleyzos-divider">
|
| 237 |
|
| 238 |
+
<section aria-labelledby="features">
|
| 239 |
+
<h2 id="features">Ключевые особенности</h2>
|
| 240 |
+
<ul class="bleyzos-features">
|
| 241 |
<li><strong>Гибридное внимание</strong> — Sliding Window Attention + Global Attention (6:1), снижает KV-cache ~в 7 раз.</li>
|
| 242 |
<li><strong>Multi-Token Prediction</strong> — 3 слоя MTP для ускорения вывода в 3 раза.</li>
|
| 243 |
<li><strong>Длинный контекст</strong> — до 1M токенов, можно подавать целые кодовые базы.</li>
|
|
|
|
| 248 |
|
| 249 |
<hr class="bleyzos-divider">
|
| 250 |
|
| 251 |
+
<section aria-labelledby="usage">
|
| 252 |
+
<h2 id="usage">Использование</h2>
|
| 253 |
<h3>Hugging Face Inference API</h3>
|
| 254 |
<pre><code class="language-python">from huggingface_hub import InferenceClient
|
| 255 |
|