Reinforcement Learning
Transformers
Safetensors
qwen2
text-generation
grpo
combinatorial-optimization
code-generation
sds
icml-2026
text-generation-inference
Instructions to use IDEALLab/Qwen2.5-Coder-14B-Instruct-GRPO-SDS-Ablation-Diversity-seed303 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IDEALLab/Qwen2.5-Coder-14B-Instruct-GRPO-SDS-Ablation-Diversity-seed303 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("IDEALLab/Qwen2.5-Coder-14B-Instruct-GRPO-SDS-Ablation-Diversity-seed303") model = AutoModelForCausalLM.from_pretrained("IDEALLab/Qwen2.5-Coder-14B-Instruct-GRPO-SDS-Ablation-Diversity-seed303", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: apache-2.0
base_model: Qwen/Qwen2.5-Coder-14B-Instruct
tags:
- reinforcement-learning
- grpo
- combinatorial-optimization
- code-generation
- sds
- icml-2026
datasets:
- SoheylM/OpenR1-SDS-10k-seed303
library_name: transformers
Qwen2.5-Coder-14B-Instruct-GRPO-SDS-Ablation-Diversity-seed303
Description
Diversity ablation (seed 303).
This model is part of the Neural Solver Synthesis project (ICML 2026). It acts as a compiled solver for the SDS problem.
Artifacts
- Training Data: SoheylM/OpenR1-SDS-10k-seed303
- Base Model: Qwen 2.5 Coder 14B