Upload fine-tuned intent detection model - 2025-06-22 22:05:48

QwenKnowledgeBase.mlpackage/Data/com.apple.CoreML/model.mlmodel

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bcccbf38e008eed54a8b9e6c0fab3b4b03142ab01a1560afc17a74ee69782567
+size 558192

QwenKnowledgeBase.mlpackage/Data/com.apple.CoreML/weights/weight.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7d3c392f9346bdc7d46803bf0e1ea3b086f74a02c3a2a61970105f72f1e11bca
+size 1544714560

QwenKnowledgeBase.mlpackage/Manifest.json

@@ -0,0 +1,18 @@
+{
+    "fileFormatVersion": "1.0.0",
+    "itemInfoEntries": {
+        "3F1423B9-49B1-4149-8134-4F3C1F1687B0": {
+            "author": "com.apple.CoreML",
+            "description": "CoreML Model Weights",
+            "name": "weights",
+            "path": "com.apple.CoreML/weights"
+        },
+        "7DBE82E2-73B4-4431-AB6B-6014D5E826A6": {
+            "author": "com.apple.CoreML",
+            "description": "CoreML Model Specification",
+            "name": "model.mlmodel",
+            "path": "com.apple.CoreML/model.mlmodel"
+        }
+    },
+    "rootModelIdentifier": "7DBE82E2-73B4-4431-AB6B-6014D5E826A6"
+}

README.md

@@ -65,7 +65,7 @@ let model = try await LLMModelFactory.shared.loadContainer(
 ## Training Details
 
 - **Fine-tuning Method**: LoRA with model fusion
-- **Export Date**: 2025-06-22T10:45:05.326944
+- **Export Date**: 2025-06-22T22:05:45.624301
 - **Fusion Completed**: True
 
 ## Expected Outputs

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b1d2d02c9d1dcdfcf7a322b33f64a71c3017ee3db47b6596b275463e156b5d78
+oid sha256:d7131fc5a349afd797454c5d369704339196f4f32caeb4cea29f482fc564bafa
 size 868628547

model_config.json

@@ -30,7 +30,7 @@
     "examples": 5000,
     "iterations": 100,
     "training_completed": true,
-    "export_timestamp": "2025-06-22T10:45:05.326944",
+    "export_timestamp": "2025-06-22T22:05:45.624301",
     "fusion_completed": true
   },
   "ios_integration": {

setup_xcode.sh

@@ -0,0 +1,27 @@
+#!/bin/bash
+# Xcode Integration Script for QwenKnowledgeBase.mlpackage
+# Run this script to automatically add the CoreML model to your Xcode project
+
+echo "🚀 Setting up CoreML model for Xcode integration..."
+
+# Check if we're in the right directory
+if [ ! -f "QwenKnowledgeBase.mlpackage" ] && [ ! -d "QwenKnowledgeBase.mlpackage" ]; then
+    echo "❌ Error: QwenKnowledgeBase.mlpackage not found in current directory"
+    echo "   Make sure you're in the correct directory"
+    exit 1
+fi
+
+echo "✅ Found QwenKnowledgeBase.mlpackage"
+echo ""
+echo "📱 Next Steps for Xcode Integration:"
+echo "1. Open your Xcode project"
+echo "2. Drag 'QwenKnowledgeBase.mlpackage' from this directory into your Xcode project"
+echo "3. In the dialog that appears:"
+echo "   - Check 'Add to targets' for your app"
+echo "   - Choose 'Create groups' (not folder references)"
+echo "4. Xcode will automatically compile the model to .mlmodelc format"
+echo ""
+echo "🎯 The model will be available in your app bundle as:"
+echo "   Bundle.main.url(forResource: "QwenKnowledgeBase", withExtension: "mlmodelc")"
+echo ""
+echo "✅ Integration complete!"

tokenizer_config.json

@@ -195,7 +195,6 @@
     "<|video_pad|>"
   ],
   "bos_token": null,
-  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- messages[0]['content'] }}\n    {%- else %}\n        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n    {%- endif %}\n    {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n    {%- else %}\n        {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role }}\n        {%- if message.content %}\n            {{- '\\n' + message.content }}\n        {%- endif %}\n        {%- for tool_call in message.tool_calls %}\n            {%- if tool_call.function is defined %}\n                {%- set tool_call = tool_call.function %}\n            {%- endif %}\n            {{- '\\n<tool_call>\\n{\"name\": \"' }}\n            {{- tool_call.name }}\n            {{- '\", \"arguments\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- '}\\n</tool_call>' }}\n        {%- endfor %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- message.content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
   "clean_up_tokenization_spaces": false,
   "eos_token": "<|im_end|>",
   "errors": "replace",