这就翻车了？Reflection 70B遭质疑基模为Llama 3，作者：重新训练

from transformers import AutoModelForCausalLM, AutoTokenizerimport torchimport matplotlib.pyplot as pltimport seaborn as snsbase_model_name = "meta-llama/Meta-Llama-3-70B-Instruct"chat_model_name = "mattshumer/Reflection-Llama-3.1-70B"base_model = AutoModelForCausalLM.from_pretrained(base_model_name, torch_dtype=torch.bfloat16)chat_model = AutoModelForCausalLM.from_pretrained(chat_model_name, torch_dtype=torch.bfloat16)def calculate_weight_diff(base_weight, chat_weight):return torch.abs(base_weight - chat_weight).mean().item()def calculate_layer_diffs(base_model, chat_model):layer_diffs = []for base_layer, chat_layer in zip(base_model.model.layers, chat_model.model.layers):layer_diff = {'input_layernorm': calculate_weight_diff(base_layer.input_layernorm.weight, chat_layer.input_layernorm.weight),# 'mlp_down_proj': calculate_weight_diff(base_layer.mlp.down_proj.weight, chat_layer.mlp.down_proj.weight),# 'mlp_gate_proj': calculate_weight_diff(base_layer.mlp.gate_proj.weight, chat_layer.mlp.gate_proj.weight),# 'mlp_up_proj': calculate_weight_diff(base_layer.mlp.up_proj.weight, chat_layer.mlp.up_proj.weight),'post_attention_layernorm': calculate_weight_diff(base_layer.post_attention_layernorm.weight, chat_layer.post_attention_layernorm.weight),'self_attn_q_proj': calculate_weight_diff(base_layer.self_attn.q_proj.weight, chat_layer.self_attn.q_proj.weight),'self_attn_k_proj': calculate_weight_diff(base_layer.self_attn.k_proj.weight, chat_layer.self_attn.k_proj.weight),'self_attn_v_proj': calculate_weight_diff(base_layer.self_attn.v_proj.weight, chat_layer.self_attn.v_proj.weight),'self_attn_o_proj': calculate_weight_diff(base_layer.self_attn.o_proj.weight, chat_layer.self_attn.o_proj.weight)}layer_diffs.append(layer_diff)return layer_diffsdef visualize_layer_diffs(layer_diffs):num_layers = len(layer_diffs)num_components = len(layer_diffs[0])fig, axs = plt.subplots(1, num_components, figsize=(24, 8))fig.suptitle(f"{base_model_name}  {chat_model_name}", fontsize=16)for i, component in enumerate(layer_diffs[0].keys()):component_diffs = [[layer_diff[component]] for layer_diff in layer_diffs]sns.heatmap(component_diffs, annot=True, fmt=".6f", cmap="YlGnBu", ax=axs[i], cbar_kws={"shrink": 0.8})axs[i].set_title(component)axs[i].set_xlabel("Layer")axs[i].set_ylabel("Difference")axs[i].set_xticks([])axs[i].set_yticks(range(num_layers))axs[i].set_yticklabels(range(num_layers))axs[i].invert_yaxis()plt.tight_layout()plt.show()layer_diffs = calculate_layer_diffs(base_model, chat_model)visualize_layer_diffs(layer_diffs)