{ "dtype": "int4", "input_info": null, "optimum_version": "2.4.0.dev0", "output_attentions": false, "quantization_config": { "_dataset_kwargs": {}, "dataset": null, "default_config": { "quant_method": "default" }, "ignored_scope": null, "num_samples": null, "processor": "/nfs/ov-share-01/data/cv_bench_cache/NATIVE_GEN-AI_MODELS/gemma-4-E2B-it/pytorch/NATIVE", "quantization_configs": { "lm_model": { "_dataset_kwargs": {}, "all_layers": null, "backup_precision": null, "bits": 4, "dataset": null, "dq_group_size": null, "dtype": "int4", "gptq": null, "group_size": 128, "group_size_fallback": null, "ignored_scope": null, "lora_correction": null, "num_samples": null, "processor": "/nfs/ov-share-01/data/cv_bench_cache/NATIVE_GEN-AI_MODELS/gemma-4-E2B-it/pytorch/NATIVE", "quant_method": "default", "ratio": 1.0, "scale_estimation": null, "sensitivity_metric": null, "statistics_path": null, "sym": false, "tokenizer": "/nfs/ov-share-01/data/cv_bench_cache/NATIVE_GEN-AI_MODELS/gemma-4-E2B-it/pytorch/NATIVE" } }, "tokenizer": "/nfs/ov-share-01/data/cv_bench_cache/NATIVE_GEN-AI_MODELS/gemma-4-E2B-it/pytorch/NATIVE" }, "save_onnx_model": false, "transformers_version": "5.5.4" }