| --- |
| license: apache-2.0 |
| base_model: Qwen/Qwen2.5-Coder-7B-Instruct |
| tags: |
| - code |
| - coding-assistant |
| - arc |
| - arc-brains |
| - hackathon |
| - ppt |
| - qwen2 |
| - lora |
| - sft |
| language: |
| - en |
| pipeline_tag: text-generation |
| library_name: transformers |
| --- |
| |
| # 🌟 Arc — Friendly Coding Expert |
|
|
| > **Created by Arc Brains: Ibrahim Shaikh, Harsh Goswami, Manas Tamore, Ayush Thakur** |
|
|
| Arc is a powerful coding assistant fine-tuned from **Qwen2.5-Coder-7B-Instruct** on **253K+ high-quality coding examples**. It delivers **complete, production-ready solutions** — never patches. |
|
|
| --- |
|
|
| ## 🎯 What Arc Excels At |
|
|
| | Skill | Description | |
| |-------|-------------| |
| | 💻 **Complete Code** | Full runnable solutions with imports, error handling, docs | |
| | 🏗️ **Hackathon Projects** | Entire apps from scratch — Flask, React, CLI tools | |
| | 📊 **Presentations** | Generate PowerPoint slides programmatically | |
| | 🐛 **Debugging** | Root-cause analysis with full fixes, not band-aids | |
| | 🌐 **Multi-language** | Python, JavaScript, C++, Java, Ruby, Go, Rust, and more | |
| | 📐 **Architecture** | Full project structure with all files | |
|
|
| --- |
|
|
| ## 🚀 Quick Start |
|
|
| ```python |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| from peft import PeftModel |
| import torch |
| |
| # Load |
| base = AutoModelForCausalLM.from_pretrained( |
| "Qwen/Qwen2.5-Coder-7B-Instruct", |
| torch_dtype=torch.bfloat16, |
| device_map="auto" |
| ) |
| model = PeftModel.from_pretrained(base, "ibrahim2806/Arc") |
| tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-Coder-7B-Instruct") |
| |
| # Chat |
| messages = [ |
| {"role": "system", "content": "You are Arc, a friendly coding expert by Arc Brains."}, |
| {"role": "user", "content": "Build a full Flask REST API for a todo app with CRUD, auth, and SQLite"} |
| ] |
| |
| text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
| inputs = tokenizer(text, return_tensors="pt").to(model.device) |
| output = model.generate(**inputs, max_new_tokens=4096, temperature=0.7, do_sample=True) |
| print(tokenizer.decode(output[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True)) |
| ``` |
|
|
| --- |
|
|
| ## 📊 Training Details |
|
|
| | Parameter | Value | |
| |-----------|-------| |
| | **Base Model** | Qwen/Qwen2.5-Coder-7B-Instruct | |
| | **Method** | QLoRA (4-bit NF4) | |
| | **LoRA Rank** | 64 | |
| | **LoRA Alpha** | 128 | |
| | **Target Modules** | q/k/v/o_proj, gate/up/down_proj | |
| | **Learning Rate** | 2e-4 (cosine decay) | |
| | **Epochs** | 3 | |
| | **Effective Batch Size** | 32 | |
| | **Max Sequence Length** | 4096 | |
| | **Total Training Samples** | ~253,000 | |
| | **Optimizer** | AdamW | |
| | **Precision** | BF16 | |
|
|
| --- |
|
|
| ## 📚 Training Datasets |
|
|
| | Dataset | Samples | What It Teaches | |
| |---------|---------|-----------------| |
| | [m-a-p/Code-Feedback](https://huggingface.co/datasets/m-a-p/Code-Feedback) | 68K | Multi-turn debugging, project building, iterative refinement | |
| | [Magicoder-Evol-Instruct-110K](https://huggingface.co/datasets/ise-uiuc/Magicoder-Evol-Instruct-110K) | 110K | Complex algorithmic & system design problems | |
| | [Magicoder-OSS-Instruct-75K](https://huggingface.co/datasets/ise-uiuc/Magicoder-OSS-Instruct-75K) | 75K | Real-world code from open-source projects | |
|
|
| --- |
|
|
| ## 🏗️ Arc Brains Team |
|
|
| Built with ❤️ by **Ibrahim Shaikh**, **Harsh Goswami**, **Manas Tamore**, and **Ayush Thakur**. |
|
|
