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parakeet-nest · Oct 21, 2024 · 0e8a362 · 0e8a362
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diff --git a/.vscode/settings.json b/.vscode/settings.json
@@ -1,8 +1,8 @@
 {
     "workbench.iconTheme": "material-icon-theme",
     "workbench.colorTheme": "GitHub Dark Colorblind (Beta)",
-    "terminal.integrated.fontSize": 10,
-    "editor.fontSize": 10,
+    "terminal.integrated.fontSize": 14,
+    "editor.fontSize": 14,
     "files.autoSave": "afterDelay",
     "files.autoSaveDelay": 1000,
     "editor.insertSpaces": true,

diff --git a/README.md b/README.md
@@ -1,35 +1,45 @@
 # Awesome SMLs
 
-This is the list of the SMLs I use on my Raspberry Pi5 (8GB RAM) with [Ollama](https://ollama.com/):
+This is the list of the SMLs I use on my Raspberry Pi5 (8GB RAM) with [Ollama](https://ollama.com/):# Awesome SMLs
 
-| Name | Size | tag | Remark | kind | URL | Good on Pi5 | Usable on Pi5 |
+This is the list of the SMLs I use on my Raspberry Pi5 (8GB RAM) with Ollama
+
+| Name | Size | Tag | Remark | Kind | URL | Good on Pi5 | Usable on Pi5 |
 | --- | --- | --- | --- | --- | --- | --- | --- |
-| CodeGemma 2b | 1.6GB | 2B | Fill-in-the-middle code completion | code | https://ollama.com/library/codegemma:2b |   | x |
-| Gemma 2b | 1.7GB | 2B |   |   | https://ollama.com/library/gemma:2b |   | x |
-| Gemma2 2b | 1.6GB | 2B |   |   | https://ollama.com/library/gemma2:2b |   | x |
-| All-Minilm 22m | 46MB | 22M | Only Embeddings | embedding | https://ollama.com/library/all-minilm:22m | x | x |
-| All-Minilm 33m | 67MB | 33M | Only Embeddings | embedding | https://ollama.com/library/all-minilm:33m | x | x |
-| DeepSeek Coder 1.3b | 776MB | 1.3B | Trained on both 87% code and 13% natural language | code | https://ollama.com/library/deepseek-coder | x | x |
-| TinyLlama 1.1b | 638MB | 1.1B |   |   | https://ollama.com/library/tinyllama | x | x |
-| TinyDolphin 1.1b | 637MB | 1.1B |   |   | https://ollama.com/library/tinydolphin | x | x |
-| Phi3 Mini | 2.4GB | 3B |   |   | https://ollama.com/library/phi3:mini |   | x |
-| Phi3.5 | 2.2GB | 3B |   |   | https://ollama.com/library/phi3.5 |   | x |
-| Granite-code 3b | 2.0GB | 3B |   | code | https://ollama.com/library/granite-code |   | x |
-| Qwen2 0.5b | 352MB | 0.5B |   |   | https://ollama.com/library/qwen2:0.5b | x | x |
-| Qwen2 1.5b | 934MB | 1.5B |   |   | https://ollama.com/library/qwen2:1.5b |   | x |
-| Qwen 0.5b | 395MB | 0.5B |   |   | https://ollama.com/library/qwen:0.5b | x | x |
-| Qwen2 Math 1.5b | 935MB | 1.5B | Specialized math language model | math | https://ollama.com/library/qwen2-math:1.5b |   | x |
-| StarCoder 1b | 726MB | 1B | Code generation model | code | https://ollama.com/library/starcoder:1b | x | x |
-| StarCoder2 3b | 1.7GB | 3B |   | code | https://ollama.com/library/starcoder2:3b |   | x |
-| Stable LM 2 1.6b | 983MB | 1.6B | LLM trained on multilingual data in English, Spanish, German, Italian, French, Portuguese, and Dutch. |   | https://ollama.com/library/stablelm2 | x | x |
-| Stable Code 3b | 1.6GB | 3B | Coding model | code | https://ollama.com/library/stable-code:3b |   | x |
-| Replete-Coder Qwen2 1.5b | 1.9GB | 1.5B | Coding capabilities + non-coding data, fully cleaned and uncensored (mat+tool? to be tested) | code | https://ollama.com/rouge/replete-coder-qwen2-1.5b:Q8 | x | x |
-| Dolphin-Phi 2.7b | 1.6GB | 2.7B | uncensored |   | https://ollama.com/library/dolphin-phi:2.7b |   | x |
-| Dolphin gemma2 2b | 1.6GB | 2B |   |   | https://ollama.com/CognitiveComputations/dolphin-gemma2:2b |   | x |
-| allenporter/xlam:1b | 873MB | 1B |   | tools | https://ollama.com/allenporter/xlam:1b |   | x |
-| sam4096/qwen2tools:0.5b | 352MB | 0.5B |   | tools | https://ollama.com/sam4096/qwen2tools:0.5b | x | x |
-| sam4096/qwen2tools:1.5b | 935MB | 1.5B |   | tools | https://ollama.com/sam4096/qwen2tools:1.5b |   | x |
-| mxbai-embed-large | 670MB | 335M | Only Embeddings | embedding | https://ollama.com/library/mxbai-embed-large:335m | x | x |
-| nomic-embed-text | 274MB | 137M | Only Embeddings | embedding | https://ollama.com/library/nomic-embed-text:v1.5 | x | x |
-| Yi Coder 1.5b | 866MB | 1.5B | Code | code | https://ollama.com/library/yi-coder:1.5b |   | x |
-| bge-m3 | 1.2GB | 567M | Only Embeddings | embedding | https://ollama.com/library/bge-m3 |   | x |
+| CodeGemma 2b | 1.6GB | 2B | Fill-in-the-middle code completion | code | [Link](https://ollama.com/library/codegemma:2b) | ❌ | ✅ |
+| Gemma 2b | 1.7GB | 2B |  |  | [Link](https://ollama.com/library/gemma:2b) | ❌ | ✅ |
+| Gemma2 2b | 1.6GB | 2B |  |  | [Link](https://ollama.com/library/gemma2:2b) | ❌ | ✅ |
+| All-Minilm 22m | 46MB | 22M | Only Embeddings | embedding | [Link](https://ollama.com/library/all-minilm:22m) | ✅ | ✅ |
+| All-Minilm 33m | 67MB | 33M | Only Embeddings | embedding | [Link](https://ollama.com/library/all-minilm:33m) | ✅ | ✅ |
+| DeepSeek Coder 1.3b | 776MB | 1.3B | Trained on both 87% code and 13% natural language | code | [Link](https://ollama.com/library/deepseek-coder) | ✅ | ✅ |
+| TinyLlama 1.1b | 638MB | 1.1B |  |  | [Link](https://ollama.com/library/tinyllama) | ✅ | ✅ |
+| TinyDolphin 1.1b | 637MB | 1.1B |  |  | [Link](https://ollama.com/library/tinydolphin) | ✅ | ✅ |
+| Phi3 Mini | 2.4GB | 3B |  |  | [Link](https://ollama.com/library/phi3:mini) | ❌ | ✅ |
+| Phi3.5 | 2.2GB | 3B |  |  | [Link](https://ollama.com/library/phi3.5) | ❌ | ✅ |
+| Granite-code 3b | 2.0GB | 3B |  | code | [Link](https://ollama.com/library/granite-code) | ❌ | ✅ |
+| Qwen2.5 0.5b | 398MB | 0.5B |  | chat, tools | [Link](https://ollama.com/library/qwen2.5:0.5b) | ✅ | ✅ |
+| Qwen2.5 1.5b | 986MB | 1.5B |  | chat, tools | [Link](https://ollama.com/library/qwen2.5:1.5b) | ❌ | ✅ |
+| Qwen2.5 3b | 1.9GB | 3B |  | chat, tools | [Link](https://ollama.com/library/qwen2.5:3b) | ❌ | ✅ |
+| Qwen2.5 Coder 1.5b | 986MB | 1.5B |  | code, tools | [Link](https://ollama.com/library/qwen2.5-coder:1.5b) | ❌ | ✅ |
+| Qwen2 0.5b | 352MB | 0.5B |  |  | [Link](https://ollama.com/library/qwen2:0.5b) | ✅ | ✅ |
+| Qwen2 1.5b | 934MB | 1.5B |  |  | [Link](https://ollama.com/library/qwen2:1.5b) | ❌ | ✅ |
+| Qwen 0.5b | 395MB | 0.5B |  |  | [Link](https://ollama.com/library/qwen:0.5b) | ✅ | ✅ |
+| Qwen2 Math 1.5b | 935MB | 1.5B | Specialized math language model | math | [Link](https://ollama.com/library/qwen2-math:1.5b) | ❌ | ✅ |
+| StarCoder 1b | 726MB | 1B | Code generation model | code | [Link](https://ollama.com/library/starcoder:1b) | ✅ | ✅ |
+| StarCoder2 3b | 1.7GB | 3B |  | code | [Link](https://ollama.com/library/starcoder2:3b) | ❌ | ✅ |
+| Stable LM 2 1.6b | 983MB | 1.6B | LLM trained on multilingual data in English, Spanish, German, Italian, French, Portuguese, and Dutch. |  | [Link](https://ollama.com/library/stablelm2) | ✅ | ✅ |
+| Stable Code 3b | 1.6GB | 3B | Coding model | code | [Link](https://ollama.com/library/stable-code:3b) | ❌ | ✅ |
+| Replete-Coder Qwen2 1.5b | 1.9GB | 1.5B | Coding capabilities + non-coding data, fully cleaned and uncensored (mat+tool? to be tested) | code | [Link](https://ollama.com/rouge/replete-coder-qwen2-1.5b:Q8) | ✅ | ✅ |
+| Dolphin-Phi 2.7b | 1.6GB | 2.7B | uncensored |  | [Link](https://ollama.com/library/dolphin-phi:2.7b) | ❌ | ✅ |
+| Dolphin gemma2 2b | 1.6GB | 2B |  |  | [Link](https://ollama.com/CognitiveComputations/dolphin-gemma2:2b) | ❌ | ✅ |
+| allenporter/xlam:1b | 873MB | 1B |  | tools | [Link](https://ollama.com/allenporter/xlam:1b) | ❌ | ✅ |
+| sam4096/qwen2tools:0.5b | 352MB | 0.5B |  | tools | [Link](https://ollama.com/sam4096/qwen2tools:0.5b) | ✅ | ✅ |
+| sam4096/qwen2tools:1.5b | 935MB | 1.5B |  | tools | [Link](https://ollama.com/sam4096/qwen2tools:1.5b) | ❌ | ✅ |
+| mxbai-embed-large | 670MB | 335M | Only Embeddings | embedding | [Link](https://ollama.com/library/mxbai-embed-large:335m) | ✅ | ✅ |
+| nomic-embed-text | 274MB | 137M | Only Embeddings | embedding | [Link](https://ollama.com/library/nomic-embed-text:v1.5) | ✅ | ✅ |
+| Yi Coder 1.5b | 866MB | 1.5B | Code | code | [Link](https://ollama.com/library/yi-coder:1.5b) | ❌ | ✅ |
+| bge-m3 | 1.2GB | 567M | Only Embeddings | embedding | [Link](https://ollama.com/library/bge-m3) | ❌ | ✅ |
+| reader-lm:0.5b | 352MB | 0.5b | convert HTML to Markdown |  | [Link](https://ollama.com/library/reader-lm:0.5b) | ✅ | ✅ |
+| reader-lm:1.5b | 935MB | 1.5b | convert HTML to Markdown |  | [Link](https://ollama.com/library/reader-lm:1.5b) | ✅ | ✅ |
+| shieldgemma:2b | 1.7GB | 2b | evaluate the safety of text |  | [Link](https://ollama.com/library/shieldgemma:2b) | ❌ | ✅ |
+| llama-guard3:1b | 1.6GB | 1b | evaluate the safety of text |  | [Link](https://ollama.com/library/llama-guard3:1b) | ❌ | ✅ |
diff --git a/data.js b/data.js
@@ -113,6 +113,46 @@ const smlData =
         "good_on_pi5": false,
         "usable_on_pi5": true
       },
+      {
+        "name": "Qwen2.5 0.5b",
+        "size": "398MB",
+        "tag": "0.5B",
+        "remark": "",
+        "kind": "chat, tools",
+        "url": "https://ollama.com/library/qwen2.5:0.5b",
+        "good_on_pi5": true,
+        "usable_on_pi5": true
+      },
+      {
+        "name": "Qwen2.5 1.5b",
+        "size": "986MB",
+        "tag": "1.5B",
+        "remark": "",
+        "kind": "chat, tools",
+        "url": "https://ollama.com/library/qwen2.5:1.5b",
+        "good_on_pi5": false,
+        "usable_on_pi5": true
+      },
+      {
+        "name": "Qwen2.5 3b",
+        "size": "1.9GB",
+        "tag": "3B",
+        "remark": "",
+        "kind": "chat, tools",
+        "url": "https://ollama.com/library/qwen2.5:3b",
+        "good_on_pi5": false,
+        "usable_on_pi5": true
+      },
+      {
+        "name": "Qwen2.5 Coder 1.5b",
+        "size": "986MB",
+        "tag": "1.5B",
+        "remark": "",
+        "kind": "code, tools",
+        "url": "https://ollama.com/library/qwen2.5-coder:1.5b",
+        "good_on_pi5": false,
+        "usable_on_pi5": true
+      },
       {
         "name": "Qwen2 0.5b",
         "size": "352MB",
@@ -292,6 +332,90 @@ const smlData =
         "url": "https://ollama.com/library/bge-m3",
         "good_on_pi5": false,
         "usable_on_pi5": true
+      },
+      {
+        "name": "reader-lm:0.5b",
+        "size": "352MB",
+        "tag": "0.5b",
+        "remark": "convert HTML to Markdown",
+        "kind": "",
+        "url": "https://ollama.com/library/reader-lm:0.5b",
+        "good_on_pi5": true,
+        "usable_on_pi5": true
+      },
+      {
+        "name": "reader-lm:1.5b",
+        "size": "935MB",
+        "tag": "1.5b",
+        "remark": "convert HTML to Markdown",
+        "kind": "",
+        "url": "https://ollama.com/library/reader-lm:1.5b",
+        "good_on_pi5": true,
+        "usable_on_pi5": true
+      },
+      {
+        "name": "shieldgemma:2b",
+        "size": "1.7GB",
+        "tag": "2b",
+        "remark": "evaluate the safety of text",
+        "kind": "",
+        "url": "https://ollama.com/library/shieldgemma:2b",
+        "good_on_pi5": false,
+        "usable_on_pi5": true
+      },
+      {
+        "name": "llama-guard3:1b",
+        "size": "1.6GB",
+        "tag": "1b",
+        "remark": "evaluate the safety of text",
+        "kind": "",
+        "url": "https://ollama.com/library/llama-guard3:1b",
+        "good_on_pi5": false,
+        "usable_on_pi5": true
       }
     ]
   }
+
+
+function generateMarkdownTable(data) {
+  const headers = [
+    'Name', 'Size', 'Tag', 'Remark', 'Kind', 'URL', 'Good on Pi5', 'Usable on Pi5'
+  ];
+
+  let markdown = `# ${data.title}\n\n${data.description}\n\n`;
+  markdown += `| ${headers.join(' | ')} |\n`;
+  markdown += `| ${headers.map(() => '---').join(' | ')} |\n`;
+
+  data.models.forEach(model => {
+    const row = [
+      model.name,
+      model.size,
+      model.tag,
+      model.remark,
+      model.kind,
+      `[Link](${model.url})`,
+      model.good_on_pi5 ? '✅' : '❌',
+      model.usable_on_pi5 ? '✅' : '❌'
+    ];
+    markdown += `| ${row.join(' | ')} |\n`;
+  });
+
+  return markdown;
+}
+
+
+
+function generate() {
+  mdContent = `# Awesome SMLs
+
+This is the list of the SMLs I use on my Raspberry Pi5 (8GB RAM) with [Ollama](https://ollama.com/):`
+
+  mdContent += generateMarkdownTable(smlData)
+  const fs = require('fs')
+  fs.writeFileSync("README.md", mdContent);
+}
+
+// Only run the main function if this script is run directly (not imported)
+if (require.main === module) {
+  generate();
+}