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README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen3-Coder-30B-A3B-Instruct
+tags:
+  - angular
+  - lora
+  - peft
+library_name: peft
+---
+
+# angular-coder-30b-a3b-lora
+
+The PEFT LoRA adapter behind `bharathmuppa/angular-coder-30b-a3b`. Apply it to `Qwen/Qwen3-Coder-30B-A3B-Instruct`:
+
+```python
+from peft import PeftModel
+from transformers import AutoModelForCausalLM, AutoTokenizer
+base = "Qwen/Qwen3-Coder-30B-A3B-Instruct"
+tok = AutoTokenizer.from_pretrained(base)
+model = AutoModelForCausalLM.from_pretrained(base, dtype="auto", device_map="auto")
+model = PeftModel.from_pretrained(model, "bharathmuppa/angular-coder-30b-a3b-lora")
+```
+
+Rank 16, alpha 16, dropout 0.05, target modules: q/k/v/o projections of every
+layer. Trained 145 optimizer steps (0.365 epochs), final eval loss
+1.3578. `train_summary.json` in this repo holds the run settings. See the
+merged model card for data and training details.