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
metadata
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: