metadata
library_name: transformers
tags:
- code
- coding-assistant
- qwen2
- lora
- fine-tuned
- full-stack
- reasoning
license: apache-2.0
language:
- en
base_model: Qwen/Qwen2.5-Coder-1.5B-Instruct
pipeline_tag: text-generation
🇮🇳 IndraCoder — AI Coding Assistant
A fine-tuned coding LLM built on Qwen2.5-Coder-1.5B-Instruct, trained on 4 curated datasets for code generation, debugging, algorithmic reasoning, and agentic tool use.
✨ Highlights
- 🧠 Chain-of-thought reasoning — Uses
<think>blocks to reason before coding - 🔧 Full-stack development — Python, JavaScript, TypeScript, React, FastAPI, and more
- 🛠️ Tool/function calling — Trained on agentic tool-use patterns
- 📦 Lightweight — 1.5B parameters, runs on consumer GPUs
Quick Start
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("RockySinghRajput/Indracoder", torch_dtype="auto", device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("RockySinghRajput/Indracoder")
messages = [
{"role": "system", "content": "You are IndraCoder, an expert AI coding assistant."},
{"role": "user", "content": "Write a Python function to find the longest palindromic substring."}
]
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.input_ids, max_new_tokens=512, temperature=0.7, top_p=0.9)
print(tokenizer.decode(output[0][len(inputs.input_ids[0]):], skip_special_tokens=True))
Model Details
| Property | Value |
|---|---|
| Base Model | Qwen/Qwen2.5-Coder-1.5B-Instruct |
| Parameters | 1.5B |
| Type | Causal Language Model (merged LoRA fine-tune) |
| Language | English |
| License | Apache 2.0 |
| Developed by | RockySinghRajput |
Training Details
Training Data
Fine-tuned on 4 curated datasets (~8,000 samples):
| Dataset | Purpose | Samples |
|---|---|---|
| glaive-code-assistant-v3 | General code generation & debugging | ~2,000 |
| evol-codealpaca-v1 | Hard algorithmic problems | ~2,000 |
| CodeFeedback-Filtered | Code reasoning & explanations | ~2,000 |
| glaive-function-calling-v2 | Agentic tool/function calling | ~2,000 |
Training Procedure
- Method: LoRA (Low-Rank Adaptation) → merged into base model
- LoRA Config: r=16, alpha=16, dropout=0.05
- Target Modules: q_proj, k_proj, v_proj, o_proj
- Epochs: 1
- Batch Size: 1 (gradient accumulation: 4, effective batch: 4)
- Learning Rate: 1e-4 (cosine schedule)
- Optimizer: paged_adamw_8bit
- Sequence Length: 512 tokens
- Precision: FP16 mixed precision
- Quantization: 4-bit NF4 (QLoRA) during training
Compute Infrastructure
- Hardware: NVIDIA T4 GPU
- Training Time: ~1 hour
Capabilities
✅ What IndraCoder Can Do
- Write code in Python, JavaScript, TypeScript, Java, C++, Go, Rust
- Debug code — find and fix bugs with explanations
- Explain code — break down complex code step by step
- Algorithm design — data structures, dynamic programming, graphs
- Full-stack development — React, FastAPI, Express, databases
- Tool/function calling — structured function calls for agentic workflows
⚠️ Limitations
- 1.5B model — smaller than GPT-4, Claude, or larger open-source models
- Not suitable for complex multi-file refactoring or very long code generation
- English only — not trained on multilingual data
- No image/file understanding — text-only model
- May hallucinate — always review generated code before using in production
❌ Out-of-Scope Use
- Production code without human review
- Security-critical applications without expert validation
- Medical, legal, or financial advice
- Generating malicious code or exploits
Evaluation
Tested on 4 qualitative benchmarks:
| Test | Task | Result |
|---|---|---|
| Full-Stack | REST API with auth in FastAPI | ✅ Generates working code |
| Algorithm | Implement LRU Cache O(1) | ✅ Correct approach |
| Debug | Fix React infinite re-render | ✅ Identifies useEffect issue |
| Tool Use | Chain function calls for file analysis | ✅ Correct tool selection |
Note: These are qualitative assessments, not standardized benchmarks.
Citation
@misc{indracoder2025,
title={IndraCoder: A Fine-tuned Coding LLM},
author={RockySinghRajput},
year={2025},
publisher={HuggingFace},
url={https://huggingface.co/RockySinghRajput/Indracoder}
}
Contact
- HuggingFace: RockySinghRajput