Overview

This repository hosts the hyunseoki/verl-math-transfer-7bi-to-3bi-fix07-pool7to1 model, an experimental math transfer model developed using the verl framework. It is based on the Qwen2ForCausalLM architecture and represents a transfer from a 7 billion parameter configuration down to a 3 billion parameter configuration, specifically optimized for mathematical tasks.

Key Characteristics

• Architecture: Qwen2ForCausalLM.
• Parameter Count: 7.6 billion parameters.
• Context Length: Supports a context length of 32768 tokens.
• Training Focus: Specialized in mathematical transfer learning experiments using the verl framework.
• Checkpoints: Includes multiple exported checkpoint revisions (e.g., step-010 to step-070), with main pointing to the latest (step-070).
• Export Format: Checkpoints are exported from verl FSDP shards into Hugging Face safetensors format.

Use Cases

This model is particularly suited for research and development in:

• Mathematical Reasoning: Applications requiring strong mathematical problem-solving abilities.
• Model Compression Research: Exploring the effectiveness of transferring capabilities from larger to smaller models while retaining performance in specific domains.
• Experimental AI: For developers and researchers interested in verl-based training and transfer learning methodologies for specialized tasks.