| { |
| "architectures": [ |
| "LagunaForCausalLM" |
| ], |
| "auto_map": { |
| "AutoConfig": "configuration_laguna.LagunaConfig", |
| "AutoModelForCausalLM": "modeling_laguna.LagunaForCausalLM" |
| }, |
| "model_type": "laguna", |
| "vocab_size": 100352, |
| "hidden_size": 4096, |
| "intermediate_size": 16384, |
| "num_hidden_layers": 70, |
| "num_attention_heads": 64, |
| "num_key_value_heads": 8, |
| "head_dim": 128, |
| "max_position_embeddings": 262144, |
| "attention_bias": false, |
| "attention_dropout": 0.0, |
| "rms_norm_eps": 1e-06, |
| "num_experts": 256, |
| "num_experts_per_tok": 16, |
| "moe_intermediate_size": 1024, |
| "shared_expert_intermediate_size": 1024, |
| "router_aux_loss_coef": 0.0, |
| "bos_token_id": 2, |
| "eos_token_id": [ |
| 2, |
| 24 |
| ], |
| "pad_token_id": 9, |
| "tie_word_embeddings": false, |
| "use_cache": true, |
| "torch_dtype": "bfloat16", |
| "gating": "per-element", |
| "rope_parameters": { |
| "full_attention": { |
| "rope_theta": 500000.0, |
| "rope_type": "yarn", |
| "factor": 64.0, |
| "original_max_position_embeddings": 4096, |
| "beta_slow": 1.0, |
| "beta_fast": 64.0, |
| "attention_factor": 1.0, |
| "partial_rotary_factor": 1.0 |
| } |
| }, |
| "moe_apply_router_weight_on_input": false, |
| "partial_rotary_factor": 1.0, |
| "mlp_layer_types": [ |
| "dense", |
| "dense", |
| "dense", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse", |
| "sparse" |
| ], |
| "use_bidirectional_attention": false, |
| "moe_routed_scaling_factor": 1.0, |
| "compression_config": { |
| "config_groups": { |
| "group_0": { |
| "format": "float-quantized", |
| "input_activations": { |
| "actorder": null, |
| "block_structure": null, |
| "dynamic": true, |
| "group_size": 128, |
| "num_bits": 8, |
| "observer": null, |
| "observer_kwargs": {}, |
| "strategy": "group", |
| "symmetric": true, |
| "type": "float" |
| }, |
| "output_activations": null, |
| "targets": [ |
| "Linear" |
| ], |
| "weights": { |
| "actorder": null, |
| "block_structure": [ |
| 128, |
| 128 |
| ], |
| "dynamic": false, |
| "group_size": null, |
| "num_bits": 8, |
| "observer": "minmax", |
| "observer_kwargs": {}, |
| "strategy": "block", |
| "symmetric": true, |
| "type": "float" |
| } |
| } |
| }, |
| "format": "float-quantized", |
| "global_compression_ratio": null, |
| "ignore": [ |
| "model.layers.0.self_attn.o_proj", |
| "model.layers.1.self_attn.o_proj", |
| "model.layers.2.self_attn.o_proj", |
| "model.layers.3.self_attn.o_proj", |
| "model.layers.3.mlp.gate", |
| "model.layers.4.self_attn.o_proj", |
| "model.layers.4.mlp.gate", |
| "model.layers.5.self_attn.o_proj", |
| "model.layers.5.mlp.gate", |
| "model.layers.6.self_attn.o_proj", |
| "model.layers.6.mlp.gate", |
| "model.layers.7.self_attn.o_proj", |
| "model.layers.7.mlp.gate", |
| "model.layers.8.self_attn.o_proj", |
| "model.layers.8.mlp.gate", |
| "model.layers.9.self_attn.o_proj", |
| "model.layers.9.mlp.gate", |
| "model.layers.10.self_attn.o_proj", |
| "model.layers.10.mlp.gate", |
| "model.layers.11.self_attn.o_proj", |
| "model.layers.11.mlp.gate", |
| "model.layers.12.self_attn.o_proj", |
| "model.layers.12.mlp.gate", |
| "model.layers.13.self_attn.o_proj", |
| "model.layers.13.mlp.gate", |
| "model.layers.14.self_attn.o_proj", |
| "model.layers.14.mlp.gate", |
| "model.layers.15.self_attn.o_proj", |
| "model.layers.15.mlp.gate", |
| "model.layers.16.self_attn.o_proj", |
| "model.layers.16.mlp.gate", |
| "model.layers.17.self_attn.o_proj", |
| "model.layers.17.mlp.gate", |
| "model.layers.18.self_attn.o_proj", |
| "model.layers.18.mlp.gate", |
| "model.layers.19.self_attn.o_proj", |
| "model.layers.19.mlp.gate", |
| "model.layers.20.self_attn.o_proj", |
| "model.layers.20.mlp.gate", |
| "model.layers.21.self_attn.o_proj", |
| "model.layers.21.mlp.gate", |
| "model.layers.22.self_attn.o_proj", |
| "model.layers.22.mlp.gate", |
| "model.layers.23.self_attn.o_proj", |
| "model.layers.23.mlp.gate", |
| "model.layers.24.self_attn.o_proj", |
| "model.layers.24.mlp.gate", |
| "model.layers.25.self_attn.o_proj", |
| "model.layers.25.mlp.gate", |
| "model.layers.26.self_attn.o_proj", |
| "model.layers.26.mlp.gate", |
| "model.layers.27.self_attn.o_proj", |
| "model.layers.27.mlp.gate", |
| "model.layers.28.self_attn.o_proj", |
| "model.layers.28.mlp.gate", |
| "model.layers.29.self_attn.o_proj", |
| "model.layers.29.mlp.gate", |
| "model.layers.30.self_attn.o_proj", |
| "model.layers.30.mlp.gate", |
| "model.layers.31.self_attn.o_proj", |
| "model.layers.31.mlp.gate", |
| "model.layers.32.self_attn.o_proj", |
| "model.layers.32.mlp.gate", |
| "model.layers.33.self_attn.o_proj", |
| "model.layers.33.mlp.gate", |
| "model.layers.34.self_attn.o_proj", |
| "model.layers.34.mlp.gate", |
| "model.layers.35.self_attn.o_proj", |
| "model.layers.35.mlp.gate", |
| "model.layers.36.self_attn.o_proj", |
| "model.layers.36.mlp.gate", |
| "model.layers.37.self_attn.o_proj", |
| "model.layers.37.mlp.gate", |
| "model.layers.38.self_attn.o_proj", |
| "model.layers.38.mlp.gate", |
| "model.layers.39.self_attn.o_proj", |
| "model.layers.39.mlp.gate", |
| "model.layers.40.self_attn.o_proj", |
| "model.layers.40.mlp.gate", |
| "model.layers.41.self_attn.o_proj", |
| "model.layers.41.mlp.gate", |
| "model.layers.42.self_attn.o_proj", |
| "model.layers.42.mlp.gate", |
| "model.layers.43.self_attn.o_proj", |
| "model.layers.43.mlp.gate", |
| "model.layers.44.self_attn.o_proj", |
| "model.layers.44.mlp.gate", |
| "model.layers.45.self_attn.o_proj", |
| "model.layers.45.mlp.gate", |
| "model.layers.46.self_attn.o_proj", |
| "model.layers.46.mlp.gate", |
| "model.layers.47.self_attn.o_proj", |
| "model.layers.47.mlp.gate", |
| "model.layers.48.self_attn.o_proj", |
| "model.layers.48.mlp.gate", |
| "model.layers.49.self_attn.o_proj", |
| "model.layers.49.mlp.gate", |
| "model.layers.50.self_attn.o_proj", |
| "model.layers.50.mlp.gate", |
| "model.layers.51.self_attn.o_proj", |
| "model.layers.51.mlp.gate", |
| "model.layers.52.self_attn.o_proj", |
| "model.layers.52.mlp.gate", |
| "model.layers.53.self_attn.o_proj", |
| "model.layers.53.mlp.gate", |
| "model.layers.54.self_attn.o_proj", |
| "model.layers.54.mlp.gate", |
| "model.layers.55.self_attn.o_proj", |
| "model.layers.55.mlp.gate", |
| "model.layers.56.self_attn.o_proj", |
| "model.layers.56.mlp.gate", |
| "model.layers.57.self_attn.o_proj", |
| "model.layers.57.mlp.gate", |
| "model.layers.58.self_attn.o_proj", |
| "model.layers.58.mlp.gate", |
| "model.layers.59.self_attn.o_proj", |
| "model.layers.59.mlp.gate", |
| "model.layers.60.self_attn.o_proj", |
| "model.layers.60.mlp.gate", |
| "model.layers.61.self_attn.o_proj", |
| "model.layers.61.mlp.gate", |
| "model.layers.62.self_attn.o_proj", |
| "model.layers.62.mlp.gate", |
| "model.layers.63.self_attn.o_proj", |
| "model.layers.63.mlp.gate", |
| "model.layers.64.self_attn.o_proj", |
| "model.layers.64.mlp.gate", |
| "model.layers.65.self_attn.o_proj", |
| "model.layers.65.mlp.gate", |
| "model.layers.66.self_attn.o_proj", |
| "model.layers.66.mlp.gate", |
| "model.layers.67.self_attn.o_proj", |
| "model.layers.67.mlp.gate", |
| "model.layers.68.self_attn.o_proj", |
| "model.layers.68.mlp.gate", |
| "model.layers.69.self_attn.o_proj", |
| "model.layers.69.mlp.gate", |
| "lm_head" |
| ], |
| "kv_cache_scheme": { |
| "actorder": null, |
| "block_structure": null, |
| "dynamic": false, |
| "group_size": null, |
| "num_bits": 8, |
| "observer": "minmax", |
| "observer_kwargs": {}, |
| "strategy": "tensor", |
| "symmetric": true, |
| "type": "float" |
| }, |
| "quant_method": "compressed-tensors", |
| "quantization_status": "compressed", |
| "sparsity_config": {}, |
| "transform_config": {}, |
| "version": "0.11.0" |
| }, |
| "quantization_config": { |
| "config_groups": { |
| "group_0": { |
| "format": "float-quantized", |
| "input_activations": { |
| "actorder": null, |
| "block_structure": null, |
| "dynamic": true, |
| "group_size": 128, |
| "num_bits": 8, |
| "observer": null, |
| "observer_kwargs": {}, |
| "strategy": "group", |
| "symmetric": true, |
| "type": "float" |
| }, |
| "output_activations": null, |
| "targets": [ |
| "Linear" |
| ], |
| "weights": { |
| "actorder": null, |
| "block_structure": [ |
| 128, |
| 128 |
| ], |
| "dynamic": false, |
| "group_size": null, |
| "num_bits": 8, |
| "observer": "minmax", |
| "observer_kwargs": {}, |
| "strategy": "block", |
| "symmetric": true, |
| "type": "float" |
| } |
| } |
| }, |
| "format": "float-quantized", |
| "global_compression_ratio": null, |
| "ignore": [ |
| "model.layers.0.self_attn.o_proj", |
| "model.layers.1.self_attn.o_proj", |
| "model.layers.2.self_attn.o_proj", |
| "model.layers.3.self_attn.o_proj", |
| "model.layers.3.mlp.gate", |
| "model.layers.4.self_attn.o_proj", |
| "model.layers.4.mlp.gate", |
| "model.layers.5.self_attn.o_proj", |
| "model.layers.5.mlp.gate", |
| "model.layers.6.self_attn.o_proj", |
| "model.layers.6.mlp.gate", |
| "model.layers.7.self_attn.o_proj", |
| "model.layers.7.mlp.gate", |
| "model.layers.8.self_attn.o_proj", |
| "model.layers.8.mlp.gate", |
| "model.layers.9.self_attn.o_proj", |
| "model.layers.9.mlp.gate", |
| "model.layers.10.self_attn.o_proj", |
| "model.layers.10.mlp.gate", |
| "model.layers.11.self_attn.o_proj", |
| "model.layers.11.mlp.gate", |
| "model.layers.12.self_attn.o_proj", |
| "model.layers.12.mlp.gate", |
| "model.layers.13.self_attn.o_proj", |
| "model.layers.13.mlp.gate", |
| "model.layers.14.self_attn.o_proj", |
| "model.layers.14.mlp.gate", |
| "model.layers.15.self_attn.o_proj", |
| "model.layers.15.mlp.gate", |
| "model.layers.16.self_attn.o_proj", |
| "model.layers.16.mlp.gate", |
| "model.layers.17.self_attn.o_proj", |
| "model.layers.17.mlp.gate", |
| "model.layers.18.self_attn.o_proj", |
| "model.layers.18.mlp.gate", |
| "model.layers.19.self_attn.o_proj", |
| "model.layers.19.mlp.gate", |
| "model.layers.20.self_attn.o_proj", |
| "model.layers.20.mlp.gate", |
| "model.layers.21.self_attn.o_proj", |
| "model.layers.21.mlp.gate", |
| "model.layers.22.self_attn.o_proj", |
| "model.layers.22.mlp.gate", |
| "model.layers.23.self_attn.o_proj", |
| "model.layers.23.mlp.gate", |
| "model.layers.24.self_attn.o_proj", |
| "model.layers.24.mlp.gate", |
| "model.layers.25.self_attn.o_proj", |
| "model.layers.25.mlp.gate", |
| "model.layers.26.self_attn.o_proj", |
| "model.layers.26.mlp.gate", |
| "model.layers.27.self_attn.o_proj", |
| "model.layers.27.mlp.gate", |
| "model.layers.28.self_attn.o_proj", |
| "model.layers.28.mlp.gate", |
| "model.layers.29.self_attn.o_proj", |
| "model.layers.29.mlp.gate", |
| "model.layers.30.self_attn.o_proj", |
| "model.layers.30.mlp.gate", |
| "model.layers.31.self_attn.o_proj", |
| "model.layers.31.mlp.gate", |
| "model.layers.32.self_attn.o_proj", |
| "model.layers.32.mlp.gate", |
| "model.layers.33.self_attn.o_proj", |
| "model.layers.33.mlp.gate", |
| "model.layers.34.self_attn.o_proj", |
| "model.layers.34.mlp.gate", |
| "model.layers.35.self_attn.o_proj", |
| "model.layers.35.mlp.gate", |
| "model.layers.36.self_attn.o_proj", |
| "model.layers.36.mlp.gate", |
| "model.layers.37.self_attn.o_proj", |
| "model.layers.37.mlp.gate", |
| "model.layers.38.self_attn.o_proj", |
| "model.layers.38.mlp.gate", |
| "model.layers.39.self_attn.o_proj", |
| "model.layers.39.mlp.gate", |
| "model.layers.40.self_attn.o_proj", |
| "model.layers.40.mlp.gate", |
| "model.layers.41.self_attn.o_proj", |
| "model.layers.41.mlp.gate", |
| "model.layers.42.self_attn.o_proj", |
| "model.layers.42.mlp.gate", |
| "model.layers.43.self_attn.o_proj", |
| "model.layers.43.mlp.gate", |
| "model.layers.44.self_attn.o_proj", |
| "model.layers.44.mlp.gate", |
| "model.layers.45.self_attn.o_proj", |
| "model.layers.45.mlp.gate", |
| "model.layers.46.self_attn.o_proj", |
| "model.layers.46.mlp.gate", |
| "model.layers.47.self_attn.o_proj", |
| "model.layers.47.mlp.gate", |
| "model.layers.48.self_attn.o_proj", |
| "model.layers.48.mlp.gate", |
| "model.layers.49.self_attn.o_proj", |
| "model.layers.49.mlp.gate", |
| "model.layers.50.self_attn.o_proj", |
| "model.layers.50.mlp.gate", |
| "model.layers.51.self_attn.o_proj", |
| "model.layers.51.mlp.gate", |
| "model.layers.52.self_attn.o_proj", |
| "model.layers.52.mlp.gate", |
| "model.layers.53.self_attn.o_proj", |
| "model.layers.53.mlp.gate", |
| "model.layers.54.self_attn.o_proj", |
| "model.layers.54.mlp.gate", |
| "model.layers.55.self_attn.o_proj", |
| "model.layers.55.mlp.gate", |
| "model.layers.56.self_attn.o_proj", |
| "model.layers.56.mlp.gate", |
| "model.layers.57.self_attn.o_proj", |
| "model.layers.57.mlp.gate", |
| "model.layers.58.self_attn.o_proj", |
| "model.layers.58.mlp.gate", |
| "model.layers.59.self_attn.o_proj", |
| "model.layers.59.mlp.gate", |
| "model.layers.60.self_attn.o_proj", |
| "model.layers.60.mlp.gate", |
| "model.layers.61.self_attn.o_proj", |
| "model.layers.61.mlp.gate", |
| "model.layers.62.self_attn.o_proj", |
| "model.layers.62.mlp.gate", |
| "model.layers.63.self_attn.o_proj", |
| "model.layers.63.mlp.gate", |
| "model.layers.64.self_attn.o_proj", |
| "model.layers.64.mlp.gate", |
| "model.layers.65.self_attn.o_proj", |
| "model.layers.65.mlp.gate", |
| "model.layers.66.self_attn.o_proj", |
| "model.layers.66.mlp.gate", |
| "model.layers.67.self_attn.o_proj", |
| "model.layers.67.mlp.gate", |
| "model.layers.68.self_attn.o_proj", |
| "model.layers.68.mlp.gate", |
| "model.layers.69.self_attn.o_proj", |
| "model.layers.69.mlp.gate", |
| "lm_head" |
| ], |
| "kv_cache_scheme": { |
| "actorder": null, |
| "block_structure": null, |
| "dynamic": false, |
| "group_size": null, |
| "num_bits": 8, |
| "observer": "minmax", |
| "observer_kwargs": {}, |
| "strategy": "tensor", |
| "symmetric": true, |
| "type": "float" |
| }, |
| "quant_method": "compressed-tensors", |
| "quantization_status": "compressed", |
| "sparsity_config": {}, |
| "transform_config": {}, |
| "version": "0.11.0" |
| }, |
| "norm_topk_prob": true, |
| "mlp_only_layers": [ |
| 0, |
| 1, |
| 2 |
| ], |
| "decoder_sparse_step": 1, |
| "sliding_window": 0 |
| } |