Instructions to use kuromaruM/kuronormal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kuromaruM/kuronormal with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "kuromaruM/kuronormal") - Notebooks
- Google Colab
- Kaggle
Upload LoRA adapter (README written by author)
Browse files- README.md +1 -1
- adapter_config.json +2 -2
- adapter_model.safetensors +1 -1
README.md
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- Method: QLoRA (4-bit)
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- Max sequence length: 512
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- Epochs: 2
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- Learning rate:
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- LoRA: r=64, alpha=128
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## Usage
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- Method: QLoRA (4-bit)
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- Max sequence length: 512
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- Epochs: 2
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- Learning rate: 2e-05
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- LoRA: r=64, alpha=128
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## Usage
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adapter_config.json
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"o_proj",
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"q_proj",
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"gate_proj",
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"down_proj",
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"k_proj",
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"v_proj",
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"up_proj"
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],
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"target_parameters": null,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"q_proj",
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"o_proj",
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"gate_proj",
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"k_proj",
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"v_proj",
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"down_proj",
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"up_proj"
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],
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"target_parameters": null,
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adapter_model.safetensors
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