---
license: apache-2.0
datasets:
- ise-uiuc/Magicoder-OSS-Instruct-75K
- ise-uiuc/Magicoder-Evol-Instruct-110K
language:
- en
- zh
- ja
- de
- es
base_model:
- Qwen/Qwen3.5-9B
tags:
- gcm
- qwen3_5
- reasoning
- qwen
library_name: transformers
---

<div align="center">
  <img src="https://cdn-uploads.huggingface.co/production/uploads/69c842686cf758859915159c/EfCpXkcGtQhv02oKAy2La.png" width="700">
</div>

# GCM Mark II
 
GCM Mark II is a QLoRA fine-tune of **Qwen3.5-9B**, trained to improve coding reliability — specifically constraint-following, edge-case handling, and reducing invented/hallucinated API usage.

<div align="center">
  <img src="https://cdn-uploads.huggingface.co/production/uploads/69c842686cf758859915159c/bfE9PX1C-gomjWpF1JJuE.png" width="700">
</div>

 

## Model Details
 
- **Base model:** Qwen3.5-9B
- **Fine-tuning method:** QLoRA & CPT
- **Tokens trained:** ~2.5 Million
- **Training data:** [`ise-uiuc/Magicoder-Evol-Instruct-110K`](https://huggingface.co/datasets/ise-uiuc/Magicoder-Evol-Instruct-110K) (partial epoch)
- **License:** Apache 2.0
 
## Intended Use
  
- General-purpose code generation and coding assistance across multiple backend languages (Python, JavaScript, Go, C, C++, Java, Rust tested directly)
- Frontend code generation is not as reliable, future GCM models will work on this more

## How to Use
 
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
 
model = AutoModelForCausalLM.from_pretrained("OPENGCM/GCM-MARK-II", device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("OPENGCM/GCM-MARK-II")
 
messages = [{"role": "user", "content": "Write a function to check if a binary tree is balanced."}]
inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
outputs = model.generate(inputs, max_new_tokens=1024)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```
 
## Citation / Attribution
 
Base model: Qwen3.5-9B (Qwen team).
Training data: Magicoder-Evol-Instruct-110K (ise-uiuc).

# Ollama / GGUF Support
OpenGCM is actively working on .gguf files for quantized versions of GCM Mark II. Stay tuned!