PROMPT RECORD图像记录
/目标 按照 NVIDIA 教程在本地对 FLUX 模型进行微调，自主排查问题，自动恢复长时间运行的任务，并通过生成图像来验证最终模型。 教程: https://t.co/IMoDbrvltC...
中文说明
/目标 按照 NVIDIA 教程在本地对 FLUX 模型进行微调，自主排查问题，自动恢复长时间运行的任务，并通过生成图像来验证最终模型。 教程: https://t.co/IMoDbrvltC 在接下来的约 4 个小时里，Hermes agent 自主完成了以下工作： - 下载并验证 ~30GB+ 的 FLUX 模型权重 - 构建 Docker 化的训练/推理环境 - 启动并监控 100 个 epoch 的 DreamBooth LoRA 微调 - 创建自己的恢复/续训脚本 - 为长时间运行的任务调度基于 cron 的编排 - 在无监督的情况下处理故障排查 - 编写 Python 脚本，通过 ComfyUI API 验证整个工作流 - 成功生成最终的微调图像 而且它一次性完成了所有任务！ 让我印象深刻的是 DG...
原始 Prompt
/goal Follow the NVIDIA tutorial to fine-tune a FLUX model locally, troubleshoot issues autonomously, resume long-running tasks automatically, and validate the final model by generating an image.
Tutorial: https://t.co/IMoDbrvltC
For the next ~4 hours, Hermes agent autonomously:
- downloaded and validated ~30GB+ of FLUX model weights
- built Dockerized training/inference environments
- launched and monitored 100-epoch DreamBooth LoRA fine-tuning
- created its own recovery/resume scripts
- scheduled cron-based orchestration for long-running tasks
- handled troubleshooting without supervision
- wrote Python scripts to validate the workflow through the ComfyUI API
- generated the final fine-tuned image successfully
And it completed everything in one shot!
One thing that stood out to me was how capable DGX Spark is for local AI customization workflows.
Being able to run DreamBooth LoRA fine-tuning locally on a compact AI supercomputer changes the equation for teams that want to customize foundation models for their own business requirements, proprietary datasets, products, or domain-specific use cases.
The stack was:
- NVIDIA DGX Spark
- FLUX.1-dev (12B model)
- DreamBooth LoRA fine-tuning
- ComfyUI
- Hermes Agent
- GPT-5.5 reasoning/planning
If you want to get started with DGX Spark, NVIDIA created a bunch of recipes and tutorials for different use cases: https://t.co/64aVChEhqf Just point your AI harness into the tutorial and let it do itself.
@NousResearch @NVIDIAAIDev @bfl_ai #hermes #nvidia #dgxspark #flux #Nous