初始化项目，由ModelHub XC社区提供模型

Model: VANTAR-AI/nuro-copilot-7b
Source: Original Platform

README.md

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+---
+language: en
+license: apache-2.0
+base_model: Qwen/Qwen2.5-Coder-7B-Instruct
+tags:
+  - spiking-neural-networks
+  - neuromorphic-computing
+  - code-generation
+  - lora
+  - unsloth
+  - nuro-sdk
+pipeline_tag: text-generation
+---
+
+# NeuroCopilot-7B
+
+**NeuroCopilot is the first AI coding assistant fine-tuned specifically for neuromorphic computing — turning natural language into deployable spiking neural network code for Intel Loihi 2, SpiNNaker2, and Vantar Cloud.**
+Built by [Vantar AI](https://vantar.xyz) on top of Qwen2.5-Coder-7B, it bridges the gap between traditional deep learning and the next generation of brain-inspired hardware.
+
+## Model Details
+
+- **Base model:** Qwen/Qwen2.5-Coder-7B-Instruct
+- **Fine-tuning method:** QLoRA (r=64, alpha=128) via Unsloth
+- **Training data:** ~416 (instruction, Nuro SDK code) pairs generated via OSS-Instruct from 9,654 snippets across SpikingJelly, Intel Lava, snnTorch, Norse, BindsNET, Rockpool, Nengo, and NIR
+- **Hardware:** RTX 4090 (RunPod)
+- **Quantization:** 4-bit QLoRA during training; merged to bf16 safetensors for inference
+
+## What is the Nuro SDK?
+
+Nuro is a Python SDK for building, training, and deploying spiking neural networks (SNNs) to neuromorphic hardware:
+
+
+
+## Supported Hardware Targets
+
+| Target | Description |
+|--------|-------------|
+|  | CUDA GPU (simulation) |
+|  | Intel Loihi 2 neuromorphic chip |
+|  | SpiNNaker 2 (Manchester) |
+|  | Vantar Cloud (managed neuromorphic) |
+
+## Usage
+
+
+
+## Training Details
+
+- **Epochs:** 3
+- **Batch size:** 2 (effective 16 with gradient accumulation)
+- **Learning rate:** 2e-4 (cosine schedule)
+- **Final train loss:** 0.4349
+- **Training time:** ~5.5 minutes on RTX 4090
+
+## License
+
+Apache 2.0 — same as the base Qwen2.5-Coder model.
+
+## Citation
+
+