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0000200_adapters.safetensors

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README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen2.5-Coder-7B-Instruct
+library_name: mlx
+tags:
+  - mlx
+  - lora
+  - code
+  - rhino3d
+  - rhinoscriptsyntax
+  - rhinocommon
+  - 3d-modeling
+  - cad
+  - python
+datasets:
+  - custom
+language:
+  - en
+pipeline_tag: text-generation
+model-index:
+  - name: rhino-coder-7b-lora
+    results: []
+---
+
+# Rhino Coder 7B — LoRA Adapter
+
+A LoRA adapter for [Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct), fine-tuned for **Rhino3D Python scripting** — generating correct `rhinoscriptsyntax` and `RhinoCommon` code from natural language instructions.
+
+This is the **standalone LoRA adapter** (~660 MB). For the full fused model, see [rhino-coder-7b](https://huggingface.co/quocvibui/rhino-coder-7b).
+
+## Usage
+
+### With MLX (Apple Silicon)
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load(
+    "Qwen/Qwen2.5-Coder-7B-Instruct",
+    adapter_path="quocvibui/rhino-coder-7b-lora"
+)
+
+messages = [
+    {"role": "system", "content": "You are an expert Rhino3D Python programmer. Write clean, working scripts using rhinoscriptsyntax and RhinoCommon. Include all necessary imports. Only output code, no explanations unless asked."},
+    {"role": "user", "content": "Create a 10x10 grid of spheres with radius 0.5"},
+]
+
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+output = generate(model, tokenizer, prompt=prompt, max_tokens=1024)
+print(output)
+```
+
+### As an OpenAI-compatible server
+
+```bash
+mlx_lm server \
+    --model Qwen/Qwen2.5-Coder-7B-Instruct \
+    --adapter-path quocvibui/rhino-coder-7b-lora \
+    --port 8080
+```
+
+## Adapter Details
+
+| Parameter | Value |
+|-----------|-------|
+| LoRA rank | 8 |
+| LoRA scale | 20.0 |
+| LoRA dropout | 0.0 |
+| LoRA layers | 16 / 28 |
+| Adapter size | ~660 MB |
+
+## Training Details
+
+| Parameter | Value |
+|-----------|-------|
+| Base model | Qwen2.5-Coder-7B-Instruct (4-bit) |
+| Batch size | 1 |
+| Learning rate | 1e-5 |
+| Optimizer | Adam |
+| Max sequence length | 2,048 |
+| Iterations | 9,108 (2 epochs) |
+| Validation loss | 0.184 |
+| Training time | ~1.2 hours on M2 Max |
+
+### Dataset
+
+5,060 instruction-code pairs for Rhino3D Python scripting:
+
+| Source | Count |
+|--------|-------|
+| RhinoCommon API docs | 1,355 |
+| RhinoScriptSyntax source | 926 |
+| Official samples | 93 |
+| Synthetic generation | 187 |
+| Backlabeled GitHub | 1 |
+
+## Links
+
+- [GitHub: rhino3d-SLM](https://github.com/quocvibui/rhino3d-SLM)
+- [Fused model: rhino-coder-7b](https://huggingface.co/quocvibui/rhino-coder-7b)
+- [Base model: Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct)

adapter_config.json

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+{
+    "adapter_path": "training/adapters/rhino-lora",
+    "batch_size": 1,
+    "config": null,
+    "data": "training/data",
+    "fine_tune_type": "lora",
+    "grad_accumulation_steps": 1,
+    "grad_checkpoint": false,
+    "iters": 13662,
+    "learning_rate": 2e-05,
+    "lora_parameters": {
+        "rank": 8,
+        "dropout": 0.0,
+        "scale": 20.0
+    },
+    "lr_schedule": null,
+    "mask_prompt": false,
+    "max_seq_length": 2048,
+    "model": "training/models/codeqwen-7b-4bit",
+    "num_layers": 16,
+    "optimizer": "adam",
+    "optimizer_config": {
+        "adam": {},
+        "adamw": {},
+        "muon": {},
+        "sgd": {},
+        "adafactor": {}
+    },
+    "project_name": null,
+    "report_to": null,
+    "resume_adapter_file": null,
+    "save_every": 1000,
+    "seed": 0,
+    "steps_per_eval": 500,
+    "steps_per_report": 100,
+    "test": false,
+    "test_batches": 500,
+    "train": true,
+    "val_batches": 10
+}

adapters.safetensors

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