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---
license: apache-2.0
tags:
- unsloth
- trl
- sft
- code
- reasoning
- abliterated
- baukit-abliterated
datasets:
- nvidia/OpenCodeReasoning
language:
- en
base_model:
- suayptalha/Qwen3-0.6B-Code-Expert
pipeline_tag: text-generation
library_name: transformers
---
# Qwen3-0.6B-Code-Expert (Abliterated)
This project performs full fine-tuning on the **Qwen3-0.6B** language model to enhance its code reasoning and generation capabilities. Training was conducted exclusively on the `nvidia/OpenCodeReasoning` dataset, and the model was optimized using the bfloat16 (bf16) data type.
Additionally, it has been abliterated to make it steer away from censorship.
## Training Procedure
1. **Dataset Preparation**
* `nvidia/OpenCodeReasoning` dataset was used.
* Each example consists of code snippets paired with detailed step-by-step reasoning in Chain-of-Thought (CoT) style.
2. **Model Loading and Configuration**
* Qwen3-0.6B base model weights were loaded via the `unsloth` library in bf16 precision.
* Full fine-tuning (`full_finetuning=True`) was applied to all layers for optimal adaptation to code reasoning.
3. **Supervised Fine-Tuning**
* Employed the Hugging Face TRL library with the Supervised Fine-Tuning (SFT) approach.
* The model was trained to generate correct code solutions along with the corresponding reasoning chains.
## Purpose and Outcome
* The model’s capacity for understanding, reasoning about, and generating code was significantly improved through specialized, single-dataset training in bf16 precision.
* Outputs include both intermediate reasoning steps and final code solutions, enabling transparent and interpretable code generation.
## License
This project is licensed under the Apache License 2.0. See the [LICENSE](./LICENSE) file for details.
## Support
<a href="https://www.buymeacoffee.com/suayptalha" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" style="height: 60px !important;width: 217px !important;" ></a> |