Overview

This model, laion/GLM-4_7-inferredbugs-sandboxes-maxeps-131k, is a specialized fine-tuned version of the Qwen/Qwen3-8B base model. It features 8 billion parameters and supports a substantial context length of 32768 tokens. The fine-tuning process utilized the DCAgent2/GLM-4.7-inferredbugs-sandboxes-maxeps-131k dataset, indicating a focus on specific problem domains related to inferred bugs and sandboxing scenarios.

Training Details

The model underwent training with a learning rate of 4e-05, a total batch size of 16 (across 8 devices with 2 gradient accumulation steps), and a cosine learning rate scheduler with a 0.1 warmup ratio over 7 epochs. The optimizer used was ADAMW_TORCH_FUSED with standard beta and epsilon values. This configuration suggests a deliberate approach to adapting the base model's capabilities to the nuances of the fine-tuning dataset.

Intended Use

Given its specific fine-tuning on a dataset related to "inferred bugs" and "sandboxes," this model is likely intended for use cases that involve analyzing, identifying, or interacting with systems or code within controlled, isolated environments, or for tasks related to bug detection and resolution based on inferred patterns. Developers should consider its specialized training for applications requiring nuanced understanding within these domains.