Upload README.md

README.md

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+---
+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**.