Text Generation
PEFT
Safetensors
English
French
electronics
embedded-systems
kicad
lora
sft
kiki-tuning
conversational
Instructions to use electron-rare/kiki-models-tuning-sft-kicad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use electron-rare/kiki-models-tuning-sft-kicad with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-8B") model = PeftModel.from_pretrained(base_model, "electron-rare/kiki-models-tuning-sft-kicad") - Notebooks
- Google Colab
- Kaggle
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library_name: peft
base_model: Qwen/Qwen3-8B
license: apache-2.0
tags:
- electronics
- embedded-systems
- kicad
- lora
- sft
- kiki-tuning
language:
- en
- fr
datasets:
- custom
pipeline_tag: text-generation
---
# KIKI KICAD SFT — LoRA Adapter
Fine-tuned LoRA adapter for **kicad** domain expertise, based on `Qwen/Qwen3-8B`.
Part of the [KIKI Models Tuning](https://github.com/ailiance/KIKI-models-tuning) pipeline
for the [FineFab](https://github.com/ailiance) platform.
## Training Details
| Parameter | Value |
|-----------|-------|
| Base Model | `Qwen/Qwen3-8B` |
| Method | QLoRA (4-bit NF4) |
| LoRA Rank | 16 |
| Epochs | 3 |
| Dataset | 2647 examples |
| Domain | kicad |
## Usage
```python
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-8B", device_map="auto")
model = PeftModel.from_pretrained(model, "clemsail/kiki-kicad-sft")
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-8B")
```
## License
Apache 2.0
|