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Model: AviralGusain/unity-debug-coach Source: Original Platform
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README.md
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---
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language:
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- en
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license: apache-2.0
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base_model: unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit
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tags:
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- fine-tuned
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- unity
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- game-development
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- csharp
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- debugging
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- qlora
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- lora
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- unsloth
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- gguf
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datasets: []
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pipeline_tag: text-generation
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---
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# Unity C# Debugging Coach
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A fine-tuned language model that acts as a patient debugging coach for beginner and intermediate Unity game developers. Given a Unity/C# bug description, error message, or broken code snippet, the model responds with a structured four-part explanation: identify the problem, explain why it happens, provide a concrete fix, and add a prevention tip.
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## What this model does
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When given a Unity or C# debugging question, the model responds consistently in this structure:
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1. **Problem** — briefly identifies what is likely wrong
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2. **Why it happens** — explains the root cause in beginner-friendly language
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3. **How to fix it** — provides a concrete, actionable solution (often with corrected code)
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4. **Prevention tip** — gives a best-practice note to avoid the issue in future projects
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The model stays encouraging and practical, avoiding overly academic explanations.
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## Example usage
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**System prompt (recommended):**
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```
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You are a Unity C# debugging coach. When a student describes a bug or error, respond in four parts: (1) identify the problem, (2) explain why it happens, (3) give a concrete fix, (4) add a prevention tip. Keep your tone encouraging and your explanations beginner-friendly.
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```
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**Example input:**
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```
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My player keeps falling through the floor in my 2D platformer. I have a Rigidbody2D and a BoxCollider2D on the player, and a BoxCollider2D on the ground. No errors in the console.
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```
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**Example output:**
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```
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Problem:
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Your player is passing through the floor at runtime despite having the correct collider setup.
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Why it happens:
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This is almost always a collision detection issue. By default, Unity uses Discrete collision detection, which checks for collisions at each physics step. If your player moves fast enough (especially during a fall), it can teleport past a thin collider between steps — a problem called tunneling.
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How to fix it:
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Select your player's Rigidbody2D in the Inspector and change Collision Detection from "Discrete" to "Continuous". This tells Unity to check for collisions continuously along the movement path, preventing tunneling.
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Also verify:
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- Both colliders are active and not set as triggers
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- The ground layer is not excluded in the Physics 2D settings
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Prevention tip:
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Always use Continuous collision detection for fast-moving objects like players and projectiles. Reserve Discrete for slow or stationary objects to keep performance costs low.
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```
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## Training details
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| Detail | Value |
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|---|---|
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| Base model | `unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit` |
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| Fine-tuning method | QLoRA (LoRA r=16, alpha=32) |
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| Training examples | 600 |
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| Validation examples | 120 |
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| Epochs | 3 |
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| Max sequence length | 2048 tokens |
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| Learning rate | 2e-4 (cosine schedule) |
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| Batch size | 2 (grad accum 4, effective 8) |
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| Hardware | Colab A100 |
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| Framework | Unsloth + TRL SFTTrainer |
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## Dataset
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The training data was synthetically generated using GPT-5.2-chat via OpenRouter. Each example is a conversation pair where:
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- **User message:** A Unity/C# debugging question — ranging from short error-only reports to multi-line code snippets. Questions vary across 20 issue categories (NullReferenceException, collision bugs, NavMesh issues, animation transitions, etc.), 11 project contexts (2D platformer, RPG, top-down shooter, etc.), and 3 difficulty levels (beginner, intermediate, advanced beginner).
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- **Assistant message:** A structured response following the four-part format described above.
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## GGUF / LM Studio
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A Q4_K_M quantized GGUF is available in this repository for use in LM Studio, Ollama, or any llama.cpp-compatible runtime.
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To use in LM Studio: search for this repository by username in the model search.
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## Known limitations
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- The model was trained on synthetic data only; it has not seen real student conversations. Responses are structured and reliable, but may occasionally feel slightly formal compared to human tutor replies.
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- Coverage of very advanced Unity topics (custom render pipelines, DOTS/ECS, compute shaders) is limited — the training data focused on beginner/intermediate issues.
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- The model does not have access to live Unity documentation. For up-to-date API details, cross-reference with the official Unity Manual. As the teacher noted, RAG over Unity docs would significantly improve accuracy for version-specific questions.
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- Response quality may degrade on queries that mix multiple unrelated bugs in one message.
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0]['role'] == 'system' %}
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{{- messages[0]['content'] }}
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{%- else %}
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{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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{%- endif %}
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{{- "\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>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\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" }}
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{%- else %}
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{%- if messages[0]['role'] == 'system' %}
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{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
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{%- else %}
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{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- for message in messages %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
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{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{{- '<|im_start|>' + message.role }}
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{%- if message.content %}
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{{- '\n' + message.content }}
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{%- endif %}
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{%- for tool_call in message.tool_calls %}
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{%- if tool_call.function is defined %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '\n<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{{- tool_call.arguments | tojson }}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- message.content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant\n' }}
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{%- endif %}
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config.json
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{
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": null,
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"torch_dtype": "bfloat16",
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"eos_token_id": 151645,
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"hidden_act": "silu",
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"hidden_size": 3584,
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"initializer_range": 0.02,
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"intermediate_size": 18944,
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"layer_types": [
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention"
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],
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"max_position_embeddings": 32768,
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"max_window_layers": 28,
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"model_type": "qwen2",
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"num_attention_heads": 28,
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"num_hidden_layers": 28,
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"num_key_value_heads": 4,
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"pad_token_id": 151665,
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"rms_norm_eps": 1e-06,
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"rope_parameters": {
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"rope_theta": 1000000.0,
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"rope_type": "default"
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},
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"sliding_window": null,
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"tie_word_embeddings": false,
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"unsloth_fixed": true,
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"unsloth_version": "2026.4.6",
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"use_cache": false,
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"use_sliding_window": false,
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"vocab_size": 152064
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}
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|
||||||
|
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|
||||||
|
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|
||||||
|
"model.layers.25.self_attn.q_proj.weight": "model-00018-of-00021.safetensors",
|
||||||
|
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|
||||||
|
"model.layers.25.self_attn.v_proj.weight": "model-00018-of-00021.safetensors",
|
||||||
|
"model.layers.26.input_layernorm.weight": "model-00018-of-00021.safetensors",
|
||||||
|
"model.layers.26.mlp.down_proj.weight": "model-00018-of-00021.safetensors",
|
||||||
|
"model.layers.26.mlp.gate_proj.weight": "model-00018-of-00021.safetensors",
|
||||||
|
"model.layers.26.mlp.up_proj.weight": "model-00018-of-00021.safetensors",
|
||||||
|
"model.layers.26.post_attention_layernorm.weight": "model-00018-of-00021.safetensors",
|
||||||
|
"model.layers.26.self_attn.k_proj.bias": "model-00018-of-00021.safetensors",
|
||||||
|
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|
||||||
|
"model.layers.26.self_attn.o_proj.weight": "model-00018-of-00021.safetensors",
|
||||||
|
"model.layers.26.self_attn.q_proj.bias": "model-00018-of-00021.safetensors",
|
||||||
|
"model.layers.26.self_attn.q_proj.weight": "model-00018-of-00021.safetensors",
|
||||||
|
"model.layers.26.self_attn.v_proj.bias": "model-00018-of-00021.safetensors",
|
||||||
|
"model.layers.26.self_attn.v_proj.weight": "model-00018-of-00021.safetensors",
|
||||||
|
"model.layers.27.input_layernorm.weight": "model-00018-of-00021.safetensors",
|
||||||
|
"model.layers.27.mlp.down_proj.weight": "model-00019-of-00021.safetensors",
|
||||||
|
"model.layers.27.mlp.gate_proj.weight": "model-00020-of-00021.safetensors",
|
||||||
|
"model.layers.27.mlp.up_proj.weight": "model-00020-of-00021.safetensors",
|
||||||
|
"model.layers.27.post_attention_layernorm.weight": "model-00020-of-00021.safetensors",
|
||||||
|
"model.layers.27.self_attn.k_proj.bias": "model-00020-of-00021.safetensors",
|
||||||
|
"model.layers.27.self_attn.k_proj.weight": "model-00020-of-00021.safetensors",
|
||||||
|
"model.layers.27.self_attn.o_proj.weight": "model-00020-of-00021.safetensors",
|
||||||
|
"model.layers.27.self_attn.q_proj.bias": "model-00020-of-00021.safetensors",
|
||||||
|
"model.layers.27.self_attn.q_proj.weight": "model-00020-of-00021.safetensors",
|
||||||
|
"model.layers.27.self_attn.v_proj.bias": "model-00020-of-00021.safetensors",
|
||||||
|
"model.layers.27.self_attn.v_proj.weight": "model-00020-of-00021.safetensors",
|
||||||
|
"model.norm.weight": "model-00020-of-00021.safetensors",
|
||||||
|
"lm_head.weight": "model-00021-of-00021.safetensors"
|
||||||
|
}
|
||||||
|
}
|
||||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:bd5948af71b4f56cf697f7580814c7ce8b80595ef985544efcacf716126a2e31
|
||||||
|
size 11422356
|
||||||
17
tokenizer_config.json
Normal file
17
tokenizer_config.json
Normal file
@@ -0,0 +1,17 @@
|
|||||||
|
{
|
||||||
|
"add_prefix_space": false,
|
||||||
|
"backend": "tokenizers",
|
||||||
|
"bos_token": null,
|
||||||
|
"clean_up_tokenization_spaces": false,
|
||||||
|
"eos_token": "<|im_end|>",
|
||||||
|
"errors": "replace",
|
||||||
|
"extra_special_tokens": [],
|
||||||
|
"is_local": false,
|
||||||
|
"model_max_length": 32768,
|
||||||
|
"pad_token": "<|PAD_TOKEN|>",
|
||||||
|
"padding_side": "left",
|
||||||
|
"split_special_tokens": false,
|
||||||
|
"tokenizer_class": "Qwen2Tokenizer",
|
||||||
|
"unk_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"
|
||||||
|
}
|
||||||
3
unity-debug-coach-Q4_K_M-00001-of-00006.gguf
Normal file
3
unity-debug-coach-Q4_K_M-00001-of-00006.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:384e18067b4bd3b1fc4e06a3091a741db7025ab08f0edd146c59eae49b0fb7cd
|
||||||
|
size 870500256
|
||||||
3
unity-debug-coach-Q4_K_M-00002-of-00006.gguf
Normal file
3
unity-debug-coach-Q4_K_M-00002-of-00006.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:a264cf5f45f0619fcffd08d6d15fa9ae1e9380c1191d5d68d5d8b76aa0a32f2a
|
||||||
|
size 895488576
|
||||||
3
unity-debug-coach-Q4_K_M-00003-of-00006.gguf
Normal file
3
unity-debug-coach-Q4_K_M-00003-of-00006.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:279d8517d7b09753d75d27ecaebcb1c6cbac8cd634b6b534b9077277978fda21
|
||||||
|
size 899168544
|
||||||
3
unity-debug-coach-Q4_K_M-00004-of-00006.gguf
Normal file
3
unity-debug-coach-Q4_K_M-00004-of-00006.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:bbd99b71c6e4dd0d682a45679898ccdbd69435cdae3bf837196fd6b26f285c22
|
||||||
|
size 877984416
|
||||||
3
unity-debug-coach-Q4_K_M-00005-of-00006.gguf
Normal file
3
unity-debug-coach-Q4_K_M-00005-of-00006.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:37a6858e920c295e44adb137226675d8d0f9e760caa23d047842bca0c6e356c3
|
||||||
|
size 858726560
|
||||||
3
unity-debug-coach-Q4_K_M-00006-of-00006.gguf
Normal file
3
unity-debug-coach-Q4_K_M-00006-of-00006.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:f20c5cd0b1199be4e5ea449c359ff1aa84d97a59520857e66e7a56f2aa31e558
|
||||||
|
size 281205792
|
||||||
Reference in New Issue
Block a user