初始化项目，由ModelHub XC社区提供模型

Model: campedersen/cad0
Source: Original Platform

.gitattributes

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README.md

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+---
+license: mit
+base_model: Qwen/Qwen2.5-Coder-7B-Instruct
+tags:
+  - text-to-cad
+  - cad
+  - 3d-modeling
+  - parametric
+  - lora
+  - qwen2
+language:
+  - en
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+# cad0
+
+**cad0** is a fine-tuned language model for text-to-CAD generation. Given a natural
+language description of a mechanical part, it generates [Compact
+IR](https://github.com/ecto/vcad) — a token-efficient domain-specific
+language for parametric 3D geometry.
+
+## Demo
+
+Try it: [**cad0-demo on HuggingFace
+Spaces**](https://huggingface.co/spaces/campedersen/cad0-demo)
+
+For browser/offline use:
+[**cad0-mini**](https://huggingface.co/campedersen/cad0-mini) (0.5B, ONNX quantized)
+
+## What It Does
+
+```
+Input:  "50x30mm mounting plate with 4 corner holes"
+Output: C 50 30 5
+        Y 2.5 10
+        T 1 5 5 0
+        D 0 2
+        ...
+```
+
+The Compact IR output can be parsed and evaluated by the [vcad
+kernel](https://github.com/ecto/vcad) to produce editable parametric
+geometry.
+
+## Supported Part Types
+
+| Family | Examples |
+|--------|----------|
+| Bracket | L-brackets, Z-brackets, mounting plates |
+| Standoff | Cylindrical spacers, threaded standoffs |
+| Enclosure | Boxes, vented enclosures, rounded shells |
+| Gear | Spur gears, hubs |
+| Flange | Bolt circles, blind flanges |
+| Clip | Snap clips, spring clips |
+
+## Usage
+
+### With Transformers + PEFT
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+
+base_model = AutoModelForCausalLM.from_pretrained(
+    "Qwen/Qwen2.5-Coder-7B-Instruct",
+    torch_dtype="auto",
+    device_map="auto"
+)
+model = PeftModel.from_pretrained(base_model, "campedersen/cad0")
+tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-Coder-7B-Instruct")
+
+prompt = "50x30mm mounting plate with 4 corner holes"
+messages = [{"role": "user", "content": prompt}]
+text = tokenizer.apply_chat_template(messages, tokenize=False,
+add_generation_prompt=True)
+
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=256, temperature=0.1,
+do_sample=True)
+ir = tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:],
+skip_special_tokens=True)
+print(ir)
+```
+
+### API Endpoint
+
+```
+curl -X POST https://ecto--cad0-training-inference-infer.modal.run \
+  -H "Content-Type: application/json" \
+  -d '{"prompt": "L-bracket with mounting holes", "temperature": 0.1}'
+```
+
+## Compact IR Reference
+
+```
+┌──────────────┬──────────────┬──────────────────────────────────┐
+│      Op      │    Syntax    │           Description            │
+├──────────────┼──────────────┼──────────────────────────────────┤
+│ Cube         │ C x y z      │ Box with dimensions x, y, z (mm) │
+├──────────────┼──────────────┼──────────────────────────────────┤
+│ Cylinder     │ Y r h        │ Cylinder with radius r, height h │
+├──────────────┼──────────────┼──────────────────────────────────┤
+│ Sphere       │ S r          │ Sphere with radius r             │
+├──────────────┼──────────────┼──────────────────────────────────┤
+│ Cone         │ K r1 r2 h    │ Cone/frustum                     │
+├──────────────┼──────────────┼──────────────────────────────────┤
+│ Translate    │ T n x y z    │ Move node n by offset            │
+├──────────────┼──────────────┼──────────────────────────────────┤
+│ Rotate       │ R n rx ry rz │ Rotate node n (degrees)          │
+├──────────────┼──────────────┼──────────────────────────────────┤
+│ Scale        │ X n sx sy sz │ Scale node n                     │
+├──────────────┼──────────────┼──────────────────────────────────┤
+│ Union        │ U a b        │ Boolean union                    │
+├──────────────┼──────────────┼──────────────────────────────────┤
+│ Difference   │ D a b        │ Boolean subtraction              │
+├──────────────┼──────────────┼──────────────────────────────────┤
+│ Intersection │ I a b        │ Boolean intersection             │
+├──────────────┼──────────────┼──────────────────────────────────┤
+│ Shell        │ SH n t       │ Hollow out with wall thickness t │
+├──────────────┼──────────────┼──────────────────────────────────┤
+│ Fillet       │ F n r        │ Round edges with radius r        │
+├──────────────┼──────────────┼──────────────────────────────────┤
+│ Chamfer      │ CH n d       │ Bevel edges with distance d      │
+└──────────────┴──────────────┴──────────────────────────────────┘
+```
+
+Nodes are 0-indexed; each line creates a new node.
+
+## Training
+
+```
+┌───────────────────┬───────────────────────────┐
+│     Parameter     │           Value           │
+├───────────────────┼───────────────────────────┤
+│ Base model        │ Qwen2.5-Coder-7B-Instruct │
+├───────────────────┼───────────────────────────┤
+│ Method            │ QLoRA (4-bit NF4)         │
+├───────────────────┼───────────────────────────┤
+│ LoRA rank         │ 64                        │
+├───────────────────┼───────────────────────────┤
+│ LoRA alpha        │ 128                       │
+├───────────────────┼───────────────────────────┤
+│ Training examples │ 530,531                   │
+├───────────────────┼───────────────────────────┤
+│ Epochs            │ 1                         │
+├───────────────────┼───────────────────────────┤
+│ Batch size        │ 64 (effective)            │
+├───────────────────┼───────────────────────────┤
+│ Learning rate     │ 2e-4 (cosine)             │
+├───────────────────┼───────────────────────────┤
+│ Hardware          │ 1x NVIDIA H100 80GB       │
+├───────────────────┼───────────────────────────┤
+│ Training time     │ 9h 15m                    │
+└───────────────────┴───────────────────────────┘
+```
+
+## Evaluation
+
+```
+┌──────────────────────────┬───────────────────────────┐
+│          Metric          │           Value           │
+├──────────────────────────┼───────────────────────────┤
+│ Final eval loss          │ 0.324                     │
+├──────────────────────────┼───────────────────────────┤
+│ In-distribution accuracy │ 75%                       │
+├──────────────────────────┼───────────────────────────┤
+│ Out-of-distribution      │ Limited (see Limitations) │
+└──────────────────────────┴───────────────────────────┘
+```
+
+## Limitations
+
+- Training bias: May add features (holes, fillets) to simple primitives — training
+data weighted toward complex manufactured parts
+- Dimension ambiguity: Occasionally confuses radius vs diameter for cylinders
+- Limited primitives: No native hexagon support; hex shapes require boolean
+workarounds
+- OOD generalization: Struggles with part types not in training distribution
+
+## Related
+
+- https://github.com/ecto/vcad — Open-source parametric CAD with custom BRep
+kernel
+- https://vcad.io — Web app with cad0 integration
+- https://huggingface.co/campedersen/cad0-mini — 0.5B distilled model for browser
+inference
+
+## Citation
+
+@misc{cad0,
+  author = {Cam Pedersen},
+  title = {cad0: Text-to-CAD Language Model},
+  year = {2026},
+  publisher = {HuggingFace},
+  url = {https://huggingface.co/campedersen/cad0}
+}
+
+## License
+
+MIT
+

added_tokens.json

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config.json

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+{
+  "_name_or_path": "Qwen/Qwen2.5-Coder-7B",
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "hidden_act": "silu",
+  "hidden_size": 3584,
+  "initializer_range": 0.02,
+  "intermediate_size": 18944,
+  "max_position_embeddings": 32768,
+  "max_window_layers": 28,
+  "model_type": "qwen2",
+  "num_attention_heads": 28,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 4,
+  "quantization_config": {
+    "_load_in_4bit": true,
+    "_load_in_8bit": false,
+    "bnb_4bit_compute_dtype": "bfloat16",
+    "bnb_4bit_quant_storage": "uint8",
+    "bnb_4bit_quant_type": "nf4",
+    "bnb_4bit_use_double_quant": false,
+    "llm_int8_enable_fp32_cpu_offload": false,
+    "llm_int8_has_fp16_weight": false,
+    "llm_int8_skip_modules": null,
+    "llm_int8_threshold": 6.0,
+    "load_in_4bit": true,
+    "load_in_8bit": false,
+    "quant_method": "bitsandbytes"
+  },
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.47.0",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 152064
+}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "max_new_tokens": 2048,
+  "transformers_version": "4.47.0"
+}

handler.py

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+"""
+Custom handler for cad0 HuggingFace Inference Endpoint.
+
+This loads the Qwen2.5-Coder-7B-Instruct base model with the cad0 LoRA adapter.
+Upload this file to the campedersen/cad0 model repo.
+"""
+
+from typing import Dict, Any
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
+
+
+class EndpointHandler:
+    def __init__(self, path: str = ""):
+        """Load model and tokenizer."""
+        # Base model that cad0 was fine-tuned from
+        base_model = "Qwen/Qwen2.5-Coder-7B-Instruct"
+
+        # Load tokenizer from base model
+        self.tokenizer = AutoTokenizer.from_pretrained(
+            base_model,
+            trust_remote_code=True
+        )
+
+        # Quantization config for efficient inference
+        bnb_config = BitsAndBytesConfig(
+            load_in_4bit=True,
+            bnb_4bit_compute_dtype=torch.float16,
+        )
+
+        # Load the fine-tuned model (path points to the model repo)
+        self.model = AutoModelForCausalLM.from_pretrained(
+            path,
+            quantization_config=bnb_config,
+            trust_remote_code=True,
+            device_map="auto",
+            low_cpu_mem_usage=True,
+        )
+
+        self.model.eval()
+
+    def __call__(self, data: Dict[str, Any]) -> Dict[str, Any]:
+        """
+        Handle inference request.
+
+        Expected input format:
+        {
+            "inputs": "prompt text or chat-formatted text",
+            "parameters": {
+                "max_new_tokens": 256,
+                "temperature": 0.1,
+                "do_sample": true,
+                "return_full_text": false
+            }
+        }
+        """
+        inputs = data.get("inputs", "")
+        parameters = data.get("parameters", {})
+
+        # Default parameters
+        max_new_tokens = parameters.get("max_new_tokens", 256)
+        temperature = parameters.get("temperature", 0.1)
+        do_sample = parameters.get("do_sample", temperature > 0)
+        return_full_text = parameters.get("return_full_text", False)
+
+        # Tokenize
+        encoded = self.tokenizer(inputs, return_tensors="pt").to(self.model.device)
+        input_length = encoded.input_ids.shape[1]
+
+        # Generate
+        with torch.no_grad():
+            outputs = self.model.generate(
+                **encoded,
+                max_new_tokens=max_new_tokens,
+                temperature=temperature if temperature > 0 else 1.0,
+                do_sample=do_sample,
+                pad_token_id=self.tokenizer.eos_token_id,
+                eos_token_id=self.tokenizer.eos_token_id,
+            )
+
+        # Decode
+        if return_full_text:
+            generated_text = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
+        else:
+            generated_text = self.tokenizer.decode(
+                outputs[0][input_length:],
+                skip_special_tokens=True
+            )
+
+        return {"generated_text": generated_text}

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+}

requirements.txt

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+# Requirements for cad0 HuggingFace Inference Endpoint
+# Upload as requirements.txt to the campedersen/cad0 model repo
+transformers>=4.44.0
+torch>=2.0.0
+accelerate>=0.34.0
+bitsandbytes>=0.46.0

special_tokens_map.json

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+{
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+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
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+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:145191e3b102f64e84dab1926006ee71528c1ea536df048ef9ff6c48d01f95de
+size 11421995

tokenizer_config.json

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+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
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+  "errors": "replace",
+  "extra_special_tokens": {},
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+  "pad_token": "<|endoftext|>",
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+  "tokenizer_class": "Qwen2Tokenizer",
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+}