| license: apache-2.0 | |
| base_model: Qwen/Qwen3-0.6B-Base | |
| tags: | |
| - dpo | |
| - fdpo | |
| - math | |
| - code | |
| - qwen3 | |
| - reasoning | |
| datasets: | |
| - albertfares/MNLP_M3_dpo_dataset | |
| language: | |
| - en | |
| pipeline_tag: text-generation | |
| # MNLP M3 fDPO Model (69k samples) | |
| This model is a fine-tuned version of [Qwen/Qwen3-0.6B-Base](https://huggingface.co/Qwen/Qwen3-0.6B-Base) using **filtered Direct Preference Optimization (fDPO)** on the [MNLP M3 DPO dataset](https://huggingface.co/datasets/albertfares/MNLP_M3_dpo_dataset). | |
| ## Model Details | |
| - **Base Model**: Qwen/Qwen3-0.6B-Base | |
| - **Training Method**: fDPO (filtered Direct Preference Optimization) | |
| - **Dataset**: MNLP M3 mixed dataset (~69k samples) | |
| - **Format**: SafeTensors (secure format) | |
| ## Usage | |
| ```python | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| model = AutoModelForCausalLM.from_pretrained("albertfares/MNLP_M3_dpo_model_69k") | |
| tokenizer = AutoTokenizer.from_pretrained("albertfares/MNLP_M3_dpo_model_69k") | |
| ``` | |
| This model uses SafeTensors format for enhanced security and faster loading. | |