Instructions to use mc9901708/CadQuery-Qwen3.5-4B-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mc9901708/CadQuery-Qwen3.5-4B-LoRA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-4B-Base") model = PeftModel.from_pretrained(base_model, "mc9901708/CadQuery-Qwen3.5-4B-LoRA") - Notebooks
- Google Colab
- Kaggle
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Download README.md from mc9901708/CadQuery-Qwen3.5-4B-LoRA: direct link, hf CLI and curl.
- Browser
- Download file 275 Bytes
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https://huggingface.co/mc9901708/CadQuery-Qwen3.5-4B-LoRA/resolve/main/README.md
- Command line
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hf download hf://mc9901708/CadQuery-Qwen3.5-4B-LoRA/README.md
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curl -L -o README.md https://huggingface.co/mc9901708/CadQuery-Qwen3.5-4B-LoRA/resolve/main/README.md
275 Bytes
| license: apache-2.0 | |
| language: | |
| - de | |
| base_model: | |
| - Qwen/Qwen3.5-4B | |
| library_name: peft | |
| datasets: | |
| - mc9901708/CadQuery-Bauteilbeschreibungen-DE | |
| ## Project Repository | |
| Source code, training notebook and evaluation results: | |
| https://github.com/mc990-ai/CadQuery-Qwen3.5-4B |