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| Name | Quant method | Size |
|---|---|---|
| Qwen2.5-1.5B-Instruct-Ja-SFT.Q2_K.gguf | Q2_K | 0.63GB |
| Qwen2.5-1.5B-Instruct-Ja-SFT.Q3_K_S.gguf | Q3_K_S | 0.71GB |
| Qwen2.5-1.5B-Instruct-Ja-SFT.Q3_K.gguf | Q3_K | 0.77GB |
| Qwen2.5-1.5B-Instruct-Ja-SFT.Q3_K_M.gguf | Q3_K_M | 0.77GB |
| Qwen2.5-1.5B-Instruct-Ja-SFT.Q3_K_L.gguf | Q3_K_L | 0.82GB |
| Qwen2.5-1.5B-Instruct-Ja-SFT.IQ4_XS.gguf | IQ4_XS | 0.84GB |
| Qwen2.5-1.5B-Instruct-Ja-SFT.Q4_0.gguf | Q4_0 | 0.87GB |
| Qwen2.5-1.5B-Instruct-Ja-SFT.IQ4_NL.gguf | IQ4_NL | 0.88GB |
| Qwen2.5-1.5B-Instruct-Ja-SFT.Q4_K_S.gguf | Q4_K_S | 0.88GB |
| Qwen2.5-1.5B-Instruct-Ja-SFT.Q4_K.gguf | Q4_K | 0.92GB |
| Qwen2.5-1.5B-Instruct-Ja-SFT.Q4_K_M.gguf | Q4_K_M | 0.92GB |
| Qwen2.5-1.5B-Instruct-Ja-SFT.Q4_1.gguf | Q4_1 | 0.95GB |
| Qwen2.5-1.5B-Instruct-Ja-SFT.Q5_0.gguf | Q5_0 | 1.02GB |
| Qwen2.5-1.5B-Instruct-Ja-SFT.Q5_K_S.gguf | Q5_K_S | 1.02GB |
| Qwen2.5-1.5B-Instruct-Ja-SFT.Q5_K.gguf | Q5_K | 1.05GB |
| Qwen2.5-1.5B-Instruct-Ja-SFT.Q5_K_M.gguf | Q5_K_M | 1.05GB |
| Qwen2.5-1.5B-Instruct-Ja-SFT.Q5_1.gguf | Q5_1 | 1.1GB |
| Qwen2.5-1.5B-Instruct-Ja-SFT.Q6_K.gguf | Q6_K | 1.19GB |
| Qwen2.5-1.5B-Instruct-Ja-SFT.Q8_0.gguf | Q8_0 | 1.53GB |
!git clone https://github.com/llm-jp/llm-jp-eval.git
!cd llm-jp-eval && pip install -e .
!cd llm-jp-eval && python scripts/preprocess_dataset.py --dataset-name all --output-dir ./dataset_dir
!cd llm-jp-eval && python scripts/evaluate_llm.py -cn config.yaml model.pretrained_model_name_or_path=jaeyong2/Qwen2.5-1.5B-Instruct-JaMagpie-Preview tokenizer.pretrained_model_name_or_path=jaeyong2/Qwen2.5-1.5B-Instruct-JaMagpie-Preview dataset_dir=./dataset_dir/1.4.1/evaluation/test| llm-jp-eval | Qwen2.5-1.5B-Instruct | google/gemma-2-2b-jpn-it | finetuning-model |
|---|---|---|---|
| AVG | 0.4343 | 0.4315 | 0.4540 |
| CG | 0.0600 | 0.0000 | 0.1500 |
| EL | 0.3952 | 0.3222 | 0.4106 |
| FA | 0.0690 | 0.0846 | 0.0000 |
| HE | 0.4400 | 0.4350 | 0.4300 |
| MC | 0.6800 | 0.6000 | 0.6400 |
| MR | 0.4700 | 0.4900 | 0.5800 |
| MT | 0.6137 | 0.7666 | 0.7915 |
| NLI | 0.5500 | 0.5260 | 0.4440 |
| QA | 0.2443 | 0.2813 | 0.3054 |
| RC | 0.8208 | 0.8097 | 0.7881 |