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nabin2004
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Model Details
Model Provider
nabin2004
Model Tree
Qwen/Qwen2.5-Coder-7B-Instruct
Input Modalities
Output Modalities
Supported Functionality
This adapter is trained on top of Qwen/Qwen2.5-Coder-7B-Instruct (Apache 2.0). See docs/MODEL_SELECTION.md for the selection rationale.
Fine-tuned on nabin2004/AOS-Trajectories using the AOS Phase 1 SFT trainer (apps/sft).
python
import osimport torchfrom peft import PeftModelfrom transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfigtoken = os.environ.get("HF_TOKEN")base_id = "Qwen/Qwen2.5-Coder-7B-Instruct"adapter_id = "nabin2004/AOS-qwen25-coder-7b-manim-sft"bnb = BitsAndBytesConfig(load_in_4bit=True,bnb_4bit_use_double_quant=True,bnb_4bit_quant_type="nf4",bnb_4bit_compute_dtype=torch.bfloat16,)base = AutoModelForCausalLM.from_pretrained(base_id,quantization_config=bnb,device_map="auto",torch_dtype=torch.bfloat16,token=token,)model = PeftModel.from_pretrained(base, adapter_id, token=token)tokenizer = AutoTokenizer.from_pretrained(adapter_id, token=token)model.eval()
The adapter is trained on multi-turn Code Agent tool calls, not single-turn prose. Use the AOS inference script:
bash
cd apps/sftuv run python infer.py \--adapter-dir nabin2004/AOS-qwen25-coder-7b-manim-sft \--prompt "Create a short Manim scene explaining eigenvectors in 2D."