Instructions to use clemsail/micro-kiki-v4-sota with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use clemsail/micro-kiki-v4-sota with PEFT:
Task type is invalid.
- MLX
How to use clemsail/micro-kiki-v4-sota with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir micro-kiki-v4-sota clemsail/micro-kiki-v4-sota
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
| model: "models/Qwen3.6-35B-A3B" | |
| data: "data/micro-kiki/cpp" | |
| train: true | |
| fine_tune_type: lora | |
| iters: 500 | |
| batch_size: 1 | |
| learning_rate: 1e-5 | |
| adapter_path: "output/micro-kiki/lora-qwen36-35b-v4-sota/cpp" | |
| max_seq_length: 512 | |
| num_layers: 32 | |
| steps_per_report: 50 | |
| steps_per_eval: 100 | |
| grad_checkpoint: true | |
| lora_parameters: | |
| rank: 16 | |
| alpha: 16.0 | |
| dropout: 0.0 | |
| scale: 20.0 | |