{ "add_skip_keys": false, "dequantize_fp32": false, "dynamic_loss_threshold": null, "group_size": 0, "is_integer": true, "is_training": false, "modules_dtype_dict": {}, "modules_quant_config": {}, "modules_to_not_convert": [ ".img_out", ".proj_out", ".emb_in", ".final_layer", "patch_embed", ".time_embed", "multi_modal_projector", ".condition_embedder", ".t_embedder", "lm_head.weight", "wte", "model.embed_tokens", "lm_head", ".txt_out", "time_text_embed", ".context_embedder", ".txt_in", ".emb_out", ".norm_out", ".img_in", ".vid_in", ".x_embedder", "patch_embedding", "patch_emb", ".vid_out", ".y_embedder", "model.embed_tokens.weight", "lm_head.weight", "model.embed_tokens.weight", "model.layers.0.input_layernorm.weight", "model.layers.0.post_attention_layernorm.weight", "model.layers.1.input_layernorm.weight", "model.layers.1.post_attention_layernorm.weight", "model.layers.2.input_layernorm.weight", "model.layers.2.post_attention_layernorm.weight", "model.layers.3.input_layernorm.weight", "model.layers.3.post_attention_layernorm.weight", "model.layers.4.input_layernorm.weight", "model.layers.4.post_attention_layernorm.weight", "model.layers.5.input_layernorm.weight", "model.layers.5.post_attention_layernorm.weight", "model.layers.6.input_layernorm.weight", "model.layers.6.post_attention_layernorm.weight", "model.layers.7.input_layernorm.weight", "model.layers.7.post_attention_layernorm.weight", "model.layers.8.input_layernorm.weight", "model.layers.8.post_attention_layernorm.weight", "model.layers.9.input_layernorm.weight", "model.layers.9.post_attention_layernorm.weight", "model.layers.10.input_layernorm.weight", "model.layers.10.post_attention_layernorm.weight", "model.layers.11.input_layernorm.weight", "model.layers.11.post_attention_layernorm.weight", "model.layers.12.input_layernorm.weight", "model.layers.12.post_attention_layernorm.weight", "model.layers.13.input_layernorm.weight", "model.layers.13.post_attention_layernorm.weight", "model.layers.14.input_layernorm.weight", "model.layers.14.post_attention_layernorm.weight", "model.layers.15.input_layernorm.weight", "model.layers.15.post_attention_layernorm.weight", "model.layers.16.input_layernorm.weight", "model.layers.16.post_attention_layernorm.weight", "model.layers.17.input_layernorm.weight", "model.layers.17.post_attention_layernorm.weight", "model.layers.18.input_layernorm.weight", "model.layers.18.post_attention_layernorm.weight", "model.layers.19.input_layernorm.weight", "model.layers.19.post_attention_layernorm.weight", "model.layers.20.input_layernorm.weight", "model.layers.20.post_attention_layernorm.weight", "model.layers.21.input_layernorm.weight", "model.layers.21.post_attention_layernorm.weight", "model.layers.22.input_layernorm.weight", "model.layers.22.post_attention_layernorm.weight", "model.layers.23.input_layernorm.weight", "model.layers.23.post_attention_layernorm.weight", "model.layers.24.input_layernorm.weight", "model.layers.24.post_attention_layernorm.weight", "model.layers.25.input_layernorm.weight", "model.layers.25.post_attention_layernorm.weight", "model.norm.weight" ], "modules_to_not_use_matmul": [], "non_blocking": false, "quant_conv": false, "quant_embedding": false, "quant_method": "sdnq", "quantization_device": null, "quantized_matmul_dtype": null, "return_device": null, "sdnq_version": "0.1.9", "svd_rank": 32, "svd_steps": 8, "use_dynamic_quantization": false, "use_grad_ckpt": true, "use_quantized_matmul": true, "use_quantized_matmul_conv": false, "use_static_quantization": true, "use_stochastic_rounding": false, "use_svd": false, "weights_dtype": "uint4" }