Model Overview

The DCAgent/a1-stack_csharp is an 8 billion parameter language model, fine-tuned from the base Qwen/Qwen3-8B architecture. This model has been specifically trained on a specialized dataset, /e/scratch/jureap59/raoof1/sft_data/hf_hub/datasets--DCAgent--exp_rpt_stack-csharp_10k_glm_4.7_traces_jupiter, which suggests a strong focus on C# programming-related tasks.

Key Characteristics

• Base Model: Qwen/Qwen3-8B
• Parameter Count: 8 billion
• Context Length: 32768 tokens, enabling the processing of extensive code blocks and related documentation.
• Specialized Training: Fine-tuned on a dataset likely comprising C# code, traces, or related programming data, indicating an intended specialization in C# development contexts.

Training Details

The model underwent training with a learning rate of 4e-05, utilizing a cosine learning rate scheduler with a 0.1 warmup ratio over 7 epochs. The training was distributed across 16 devices, employing the ADAMW_TORCH_FUSED optimizer.

Intended Use Cases

Given its fine-tuning on C# specific data, this model is likely best suited for applications requiring an understanding or generation of C# code. Potential use cases include:

• C# code completion and generation.
• Code analysis and debugging assistance for C#.
• Understanding and responding to queries about C# programming logic.
• Automated report generation or documentation related to C# projects.