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README.md

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+---
+language:
+- en
+license: mit
+tags:
+- process-control
+- industrial-automation
+- qlora
+- llama
+- fine-tuned
+- mpc
+---
+
+# Experiment A — Baseline Fine-Tuning (No Predictive Context)
+
+**Paper**: LLMs as Autonomous Controllers for Multivariable Industrial Fluid Processes
+**Author**: Vidyashree Rayar — BTU Cottbus-Senftenberg
+
+Baseline: Llama 3.2-3B-Instruct fine-tuned with QLoRA on 11,975 records. Full cumulative prompt (SP+CoT+FS), no predictive horizon. Achieves 60.0% overall accuracy with 0% format and content hallucination — strongest safety performance across all experiments.
+
+## Base Model
+
+[meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) fine-tuned with QLoRA (4-bit NF4, LoRA r=16, alpha=32, rsLoRA enabled).
+
+## Code & Results
+
+[github.com/vidyashreerayar/festo-llm-process-control](https://github.com/vidyashreerayar/festo-llm-process-control)