Text Generation
Transformers
Safetensors
English
qwen2
text-to-cad
cad
3d-modeling
parametric
lora
conversational
text-generation-inference
4-bit precision
bitsandbytes
Instructions to use campedersen/cad0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use campedersen/cad0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="campedersen/cad0") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("campedersen/cad0") model = AutoModelForCausalLM.from_pretrained("campedersen/cad0") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use campedersen/cad0 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "campedersen/cad0" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "campedersen/cad0", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/campedersen/cad0
- SGLang
How to use campedersen/cad0 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "campedersen/cad0" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "campedersen/cad0", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "campedersen/cad0" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "campedersen/cad0", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use campedersen/cad0 with Docker Model Runner:
docker model run hf.co/campedersen/cad0
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README.md
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**cad0** is a fine-tuned language model for text-to-CAD generation. Given a natural
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language description of a mechanical part, it generates [Compact
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IR](https://github.com/
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language for parametric 3D geometry.
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## Demo
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```
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The Compact IR output can be parsed and evaluated by the [vcad
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kernel](https://github.com/
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geometry.
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## Supported Part Types
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## Related
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- https://github.com/
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kernel
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- https://vcad.io — Web app with cad0 integration
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- https://huggingface.co/campedersen/cad0-mini — 0.5B distilled model for browser
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**cad0** is a fine-tuned language model for text-to-CAD generation. Given a natural
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language description of a mechanical part, it generates [Compact
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IR](https://github.com/ecto/vcad) — a token-efficient domain-specific
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language for parametric 3D geometry.
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## Demo
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```
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The Compact IR output can be parsed and evaluated by the [vcad
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+
kernel](https://github.com/ecto/vcad) to produce editable parametric
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geometry.
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## Supported Part Types
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## Related
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+
- https://github.com/ecto/vcad — Open-source parametric CAD with custom BRep
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kernel
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- https://vcad.io — Web app with cad0 integration
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- https://huggingface.co/campedersen/cad0-mini — 0.5B distilled model for browser
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