DCAgent/a1-ghactions

TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kPublished:Mar 25, 2026License:otherArchitecture:Transformer Cold

DCAgent/a1-ghactions is a fine-tuned version of Qwen/Qwen3-8B, an 8 billion parameter causal language model. This model was specifically trained on the /e/scratch/jureap59/raoof1/sft_data/hf_hub/datasets--DCAgent--exp_rpt_ghactions_glm_4.7_traces_jupiter/snapshots/640f8ad849fb18ab4a07eb41d7a469a33c7811bf_thinking_preprocessed dataset. Its primary use case is expected to be related to tasks involving GitHub Actions, given its training data.

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Overview

DCAgent/a1-ghactions is a specialized language model derived from the Qwen/Qwen3-8B architecture. This model has undergone fine-tuning to adapt its capabilities for specific applications, particularly those related to GitHub Actions.

Key Capabilities

  • Fine-tuned from Qwen3-8B: Leverages the foundational strengths of the 8 billion parameter Qwen3 model.
  • Specialized Training Data: Trained on the /e/scratch/jureap59/raoof1/sft_data/hf_hub/datasets--DCAgent--exp_rpt_ghactions_glm_4.7_traces_jupiter/snapshots/640f8ad849fb18ab4a07eb41d7a469a33c7811bf_thinking_preprocessed dataset, indicating a focus on GitHub Actions-related contexts.

Good for

  • Applications requiring understanding or generation of content related to GitHub Actions.
  • Tasks that can benefit from a model fine-tuned on specific operational traces and reports.

Training Details

The model was trained with a learning rate of 4e-05 over 7 epochs, utilizing a total batch size of 16 across 16 devices. The optimizer used was AdamW_Torch_Fused with a cosine learning rate scheduler and a warmup ratio of 0.1.