Initial commit
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86
trace_model_meta/ZhipuAI/GLM-5-FP8/chat_template.jinja
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86
trace_model_meta/ZhipuAI/GLM-5-FP8/chat_template.jinja
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[gMASK]<sop>
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{%- if tools -%}
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<|system|>
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# Tools
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You may call one or more functions to assist with the user query.
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You are provided with function signatures within <tools></tools> XML tags:
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<tools>
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{% for tool in tools %}
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{{ tool | tojson(ensure_ascii=False) }}
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{% endfor %}
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</tools>
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For each function call, output the function name and arguments within the following XML format:
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<tool_call>{function-name}<arg_key>{arg-key-1}</arg_key><arg_value>{arg-value-1}</arg_value><arg_key>{arg-key-2}</arg_key><arg_value>{arg-value-2}</arg_value>...</tool_call>{%- endif -%}
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{%- macro visible_text(content) -%}
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{%- if content is string -%}
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{{- content }}
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{%- elif content is iterable and content is not mapping -%}
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{%- for item in content -%}
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{%- if item is mapping and item.type == 'text' -%}
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{{- item.text }}
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{%- elif item is string -%}
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{{- item }}
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{%- endif -%}
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{%- endfor -%}
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{%- else -%}
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{{- content }}
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{%- endif -%}
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{%- endmacro -%}
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{%- set ns = namespace(last_user_index=-1) %}
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{%- for m in messages %}
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{%- if m.role == 'user' %}
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{%- set ns.last_user_index = loop.index0 -%}
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{%- endif %}
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{%- endfor %}
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{%- for m in messages -%}
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{%- if m.role == 'user' -%}<|user|>{{ visible_text(m.content) }}
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{%- elif m.role == 'assistant' -%}
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<|assistant|>
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{%- set reasoning_content = '' %}
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{%- set content = visible_text(m.content) %}
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{%- if m.reasoning_content is string %}
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{%- set reasoning_content = m.reasoning_content %}
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{%- else %}
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{%- if '</think>' in content %}
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{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
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{%- set content = content.split('</think>')[-1].lstrip('\n') %}
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{%- endif %}
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{%- endif %}
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{%- if ((clear_thinking is defined and not clear_thinking) or loop.index0 > ns.last_user_index) and reasoning_content -%}
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{{ '<think>' + reasoning_content.strip() + '</think>'}}
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{%- else -%}
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{{ '</think>' }}
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{%- endif -%}
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{%- if content.strip() -%}
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{{ content.strip() }}
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{%- endif -%}
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{% if m.tool_calls %}
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{% for tc in m.tool_calls %}
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{%- if tc.function %}
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{%- set tc = tc.function %}
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{%- endif %}
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{{- '<tool_call>' + tc.name -}}
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{% set _args = tc.arguments %}{% for k, v in _args.items() %}<arg_key>{{ k }}</arg_key><arg_value>{{ v | tojson(ensure_ascii=False) if v is not string else v }}</arg_value>{% endfor %}</tool_call>{% endfor %}
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{% endif %}
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{%- elif m.role == 'tool' -%}
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{%- if m.content is string -%}
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{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|observation|>' }}
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{%- endif %}
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{{- '<tool_response>' }}
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{{- m.content }}
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{{- '</tool_response>' }}
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{%- else -%}
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<|observation|>{% for tr in m.content %}
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<tool_response>{{ tr.output if tr.output is defined else tr }}</tool_response>{% endfor -%}
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{% endif -%}
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{%- elif m.role == 'system' -%}
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<|system|>{{ visible_text(m.content) }}
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{%- endif -%}
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{%- endfor -%}
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{%- if add_generation_prompt -%}
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<|assistant|>{{- '</think>' if (enable_thinking is defined and not enable_thinking) else '<think>' -}}
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{%- endif -%}
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782
trace_model_meta/ZhipuAI/GLM-5-FP8/config.json
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782
trace_model_meta/ZhipuAI/GLM-5-FP8/config.json
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@@ -0,0 +1,782 @@
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{
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"architectures": [
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"GlmMoeDsaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"dtype": "bfloat16",
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"eos_token_id": [
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154820,
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154827,
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154829
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],
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"ep_size": 1,
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"first_k_dense_replace": 3,
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"hidden_act": "silu",
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"head_dim": 64,
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"hidden_size": 6144,
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"index_head_dim": 128,
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"index_n_heads": 32,
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"index_topk": 2048,
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"indexer_rope_interleave": true,
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"initializer_range": 0.02,
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"intermediate_size": 12288,
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"kv_lora_rank": 512,
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"max_position_embeddings": 202752,
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"moe_intermediate_size": 2048,
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"moe_layer_freq": 1,
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"model_type": "glm_moe_dsa",
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"n_group": 1,
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"n_routed_experts": 256,
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"n_shared_experts": 1,
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"norm_topk_prob": true,
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"num_attention_heads": 64,
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"num_experts_per_tok": 8,
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"num_hidden_layers": 78,
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"num_key_value_heads": 64,
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"num_nextn_predict_layers": 1,
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"pad_token_id": 154820,
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"pretraining_tp": 1,
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"q_lora_rank": 2048,
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"qk_head_dim": 256,
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"qk_nope_head_dim": 192,
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"qk_rope_head_dim": 64,
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"rms_norm_eps": 1e-05,
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"rope_interleave": true,
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"rope_parameters": {
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"rope_theta": 1000000,
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"rope_type": "default"
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},
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"routed_scaling_factor": 2.5,
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"scoring_func": "sigmoid",
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"tie_word_embeddings": false,
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"topk_group": 1,
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"topk_method": "noaux_tc",
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"transformers_version": "5.0.2.dev0",
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"use_cache": true,
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"v_head_dim": 256,
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"vocab_size": 154880,
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"quantization_config": {
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"activation_scheme": "dynamic",
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"fmt": "e4m3",
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"quant_method": "fp8",
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"weight_block_size": [
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128,
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128
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],
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||||
"modules_to_not_convert": [
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||||
"lm_head",
|
||||
"model.embed_tokens",
|
||||
"model.layers.0.input_layernorm",
|
||||
"model.layers.0.post_attention_layernorm",
|
||||
"model.layers.0.self_attn.indexer.k_norm",
|
||||
"model.layers.0.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.0.self_attn.indexers_proj",
|
||||
"model.layers.0.self_attn.kv_a_layernorm",
|
||||
"model.layers.0.self_attn.q_a_layernorm",
|
||||
"model.layers.1.input_layernorm",
|
||||
"model.layers.1.post_attention_layernorm",
|
||||
"model.layers.1.self_attn.indexer.k_norm",
|
||||
"model.layers.1.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.1.self_attn.indexers_proj",
|
||||
"model.layers.1.self_attn.kv_a_layernorm",
|
||||
"model.layers.1.self_attn.q_a_layernorm",
|
||||
"model.layers.2.input_layernorm",
|
||||
"model.layers.2.post_attention_layernorm",
|
||||
"model.layers.2.self_attn.indexer.k_norm",
|
||||
"model.layers.2.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.2.self_attn.indexers_proj",
|
||||
"model.layers.2.self_attn.kv_a_layernorm",
|
||||
"model.layers.2.self_attn.q_a_layernorm",
|
||||
"model.layers.3.input_layernorm",
|
||||
"model.layers.3.mlp.gate",
|
||||
"model.layers.3.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.3.post_attention_layernorm",
|
||||
"model.layers.3.self_attn.indexer.k_norm",
|
||||
"model.layers.3.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.3.self_attn.indexers_proj",
|
||||
"model.layers.3.self_attn.kv_a_layernorm",
|
||||
"model.layers.3.self_attn.q_a_layernorm",
|
||||
"model.layers.4.input_layernorm",
|
||||
"model.layers.4.mlp.gate",
|
||||
"model.layers.4.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.4.post_attention_layernorm",
|
||||
"model.layers.4.self_attn.indexer.k_norm",
|
||||
"model.layers.4.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.4.self_attn.indexers_proj",
|
||||
"model.layers.4.self_attn.kv_a_layernorm",
|
||||
"model.layers.4.self_attn.q_a_layernorm",
|
||||
"model.layers.5.input_layernorm",
|
||||
"model.layers.5.mlp.gate",
|
||||
"model.layers.5.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.5.post_attention_layernorm",
|
||||
"model.layers.5.self_attn.indexer.k_norm",
|
||||
"model.layers.5.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.5.self_attn.indexers_proj",
|
||||
"model.layers.5.self_attn.kv_a_layernorm",
|
||||
"model.layers.5.self_attn.q_a_layernorm",
|
||||
"model.layers.6.input_layernorm",
|
||||
"model.layers.6.mlp.gate",
|
||||
"model.layers.6.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.6.post_attention_layernorm",
|
||||
"model.layers.6.self_attn.indexer.k_norm",
|
||||
"model.layers.6.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.6.self_attn.indexers_proj",
|
||||
"model.layers.6.self_attn.kv_a_layernorm",
|
||||
"model.layers.6.self_attn.q_a_layernorm",
|
||||
"model.layers.7.input_layernorm",
|
||||
"model.layers.7.mlp.gate",
|
||||
"model.layers.7.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.7.post_attention_layernorm",
|
||||
"model.layers.7.self_attn.indexer.k_norm",
|
||||
"model.layers.7.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.7.self_attn.indexers_proj",
|
||||
"model.layers.7.self_attn.kv_a_layernorm",
|
||||
"model.layers.7.self_attn.q_a_layernorm",
|
||||
"model.layers.8.input_layernorm",
|
||||
"model.layers.8.mlp.gate",
|
||||
"model.layers.8.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.8.post_attention_layernorm",
|
||||
"model.layers.8.self_attn.indexer.k_norm",
|
||||
"model.layers.8.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.8.self_attn.indexers_proj",
|
||||
"model.layers.8.self_attn.kv_a_layernorm",
|
||||
"model.layers.8.self_attn.q_a_layernorm",
|
||||
"model.layers.9.input_layernorm",
|
||||
"model.layers.9.mlp.gate",
|
||||
"model.layers.9.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.9.post_attention_layernorm",
|
||||
"model.layers.9.self_attn.indexer.k_norm",
|
||||
"model.layers.9.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.9.self_attn.indexers_proj",
|
||||
"model.layers.9.self_attn.kv_a_layernorm",
|
||||
"model.layers.9.self_attn.q_a_layernorm",
|
||||
"model.layers.10.input_layernorm",
|
||||
"model.layers.10.mlp.gate",
|
||||
"model.layers.10.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.10.post_attention_layernorm",
|
||||
"model.layers.10.self_attn.indexer.k_norm",
|
||||
"model.layers.10.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.10.self_attn.indexers_proj",
|
||||
"model.layers.10.self_attn.kv_a_layernorm",
|
||||
"model.layers.10.self_attn.q_a_layernorm",
|
||||
"model.layers.11.input_layernorm",
|
||||
"model.layers.11.mlp.gate",
|
||||
"model.layers.11.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.11.post_attention_layernorm",
|
||||
"model.layers.11.self_attn.indexer.k_norm",
|
||||
"model.layers.11.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.11.self_attn.indexers_proj",
|
||||
"model.layers.11.self_attn.kv_a_layernorm",
|
||||
"model.layers.11.self_attn.q_a_layernorm",
|
||||
"model.layers.12.input_layernorm",
|
||||
"model.layers.12.mlp.gate",
|
||||
"model.layers.12.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.12.post_attention_layernorm",
|
||||
"model.layers.12.self_attn.indexer.k_norm",
|
||||
"model.layers.12.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.12.self_attn.indexers_proj",
|
||||
"model.layers.12.self_attn.kv_a_layernorm",
|
||||
"model.layers.12.self_attn.q_a_layernorm",
|
||||
"model.layers.13.input_layernorm",
|
||||
"model.layers.13.mlp.gate",
|
||||
"model.layers.13.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.13.post_attention_layernorm",
|
||||
"model.layers.13.self_attn.indexer.k_norm",
|
||||
"model.layers.13.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.13.self_attn.indexers_proj",
|
||||
"model.layers.13.self_attn.kv_a_layernorm",
|
||||
"model.layers.13.self_attn.q_a_layernorm",
|
||||
"model.layers.14.input_layernorm",
|
||||
"model.layers.14.mlp.gate",
|
||||
"model.layers.14.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.14.post_attention_layernorm",
|
||||
"model.layers.14.self_attn.indexer.k_norm",
|
||||
"model.layers.14.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.14.self_attn.indexers_proj",
|
||||
"model.layers.14.self_attn.kv_a_layernorm",
|
||||
"model.layers.14.self_attn.q_a_layernorm",
|
||||
"model.layers.15.input_layernorm",
|
||||
"model.layers.15.mlp.gate",
|
||||
"model.layers.15.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.15.post_attention_layernorm",
|
||||
"model.layers.15.self_attn.indexer.k_norm",
|
||||
"model.layers.15.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.15.self_attn.indexers_proj",
|
||||
"model.layers.15.self_attn.kv_a_layernorm",
|
||||
"model.layers.15.self_attn.q_a_layernorm",
|
||||
"model.layers.16.input_layernorm",
|
||||
"model.layers.16.mlp.gate",
|
||||
"model.layers.16.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.16.post_attention_layernorm",
|
||||
"model.layers.16.self_attn.indexer.k_norm",
|
||||
"model.layers.16.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.16.self_attn.indexers_proj",
|
||||
"model.layers.16.self_attn.kv_a_layernorm",
|
||||
"model.layers.16.self_attn.q_a_layernorm",
|
||||
"model.layers.17.input_layernorm",
|
||||
"model.layers.17.mlp.gate",
|
||||
"model.layers.17.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.17.post_attention_layernorm",
|
||||
"model.layers.17.self_attn.indexer.k_norm",
|
||||
"model.layers.17.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.17.self_attn.indexers_proj",
|
||||
"model.layers.17.self_attn.kv_a_layernorm",
|
||||
"model.layers.17.self_attn.q_a_layernorm",
|
||||
"model.layers.18.input_layernorm",
|
||||
"model.layers.18.mlp.gate",
|
||||
"model.layers.18.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.18.post_attention_layernorm",
|
||||
"model.layers.18.self_attn.indexer.k_norm",
|
||||
"model.layers.18.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.18.self_attn.indexers_proj",
|
||||
"model.layers.18.self_attn.kv_a_layernorm",
|
||||
"model.layers.18.self_attn.q_a_layernorm",
|
||||
"model.layers.19.input_layernorm",
|
||||
"model.layers.19.mlp.gate",
|
||||
"model.layers.19.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.19.post_attention_layernorm",
|
||||
"model.layers.19.self_attn.indexer.k_norm",
|
||||
"model.layers.19.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.19.self_attn.indexers_proj",
|
||||
"model.layers.19.self_attn.kv_a_layernorm",
|
||||
"model.layers.19.self_attn.q_a_layernorm",
|
||||
"model.layers.20.input_layernorm",
|
||||
"model.layers.20.mlp.gate",
|
||||
"model.layers.20.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.20.post_attention_layernorm",
|
||||
"model.layers.20.self_attn.indexer.k_norm",
|
||||
"model.layers.20.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.20.self_attn.indexers_proj",
|
||||
"model.layers.20.self_attn.kv_a_layernorm",
|
||||
"model.layers.20.self_attn.q_a_layernorm",
|
||||
"model.layers.21.input_layernorm",
|
||||
"model.layers.21.mlp.gate",
|
||||
"model.layers.21.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.21.post_attention_layernorm",
|
||||
"model.layers.21.self_attn.indexer.k_norm",
|
||||
"model.layers.21.self_attn.indexer.k_norm.bias",
|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.59.self_attn.q_a_layernorm",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.60.self_attn.kv_a_layernorm",
|
||||
"model.layers.60.self_attn.q_a_layernorm",
|
||||
"model.layers.61.input_layernorm",
|
||||
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|
||||
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|
||||
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|
||||
"model.layers.61.self_attn.indexer.k_norm",
|
||||
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|
||||
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|
||||
"model.layers.61.self_attn.kv_a_layernorm",
|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
"model.layers.62.self_attn.indexer.k_norm",
|
||||
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|
||||
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|
||||
"model.layers.62.self_attn.kv_a_layernorm",
|
||||
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|
||||
"model.layers.63.input_layernorm",
|
||||
"model.layers.63.mlp.gate",
|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.64.input_layernorm",
|
||||
"model.layers.64.mlp.gate",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.64.self_attn.kv_a_layernorm",
|
||||
"model.layers.64.self_attn.q_a_layernorm",
|
||||
"model.layers.65.input_layernorm",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.66.input_layernorm",
|
||||
"model.layers.66.mlp.gate",
|
||||
"model.layers.66.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.66.post_attention_layernorm",
|
||||
"model.layers.66.self_attn.indexer.k_norm",
|
||||
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|
||||
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|
||||
"model.layers.66.self_attn.kv_a_layernorm",
|
||||
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|
||||
"model.layers.67.input_layernorm",
|
||||
"model.layers.67.mlp.gate",
|
||||
"model.layers.67.mlp.gate.e_score_correction_bias",
|
||||
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|
||||
"model.layers.67.self_attn.indexer.k_norm",
|
||||
"model.layers.67.self_attn.indexer.k_norm.bias",
|
||||
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|
||||
"model.layers.67.self_attn.kv_a_layernorm",
|
||||
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|
||||
"model.layers.68.input_layernorm",
|
||||
"model.layers.68.mlp.gate",
|
||||
"model.layers.68.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.68.post_attention_layernorm",
|
||||
"model.layers.68.self_attn.indexer.k_norm",
|
||||
"model.layers.68.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.68.self_attn.indexers_proj",
|
||||
"model.layers.68.self_attn.kv_a_layernorm",
|
||||
"model.layers.68.self_attn.q_a_layernorm",
|
||||
"model.layers.69.input_layernorm",
|
||||
"model.layers.69.mlp.gate",
|
||||
"model.layers.69.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.69.post_attention_layernorm",
|
||||
"model.layers.69.self_attn.indexer.k_norm",
|
||||
"model.layers.69.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.69.self_attn.indexers_proj",
|
||||
"model.layers.69.self_attn.kv_a_layernorm",
|
||||
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|
||||
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|
||||
"model.layers.70.mlp.gate",
|
||||
"model.layers.70.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.70.post_attention_layernorm",
|
||||
"model.layers.70.self_attn.indexer.k_norm",
|
||||
"model.layers.70.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.70.self_attn.indexers_proj",
|
||||
"model.layers.70.self_attn.kv_a_layernorm",
|
||||
"model.layers.70.self_attn.q_a_layernorm",
|
||||
"model.layers.71.input_layernorm",
|
||||
"model.layers.71.mlp.gate",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.71.self_attn.kv_a_layernorm",
|
||||
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|
||||
"model.layers.72.input_layernorm",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.72.self_attn.kv_a_layernorm",
|
||||
"model.layers.72.self_attn.q_a_layernorm",
|
||||
"model.layers.73.input_layernorm",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.73.self_attn.kv_a_layernorm",
|
||||
"model.layers.73.self_attn.q_a_layernorm",
|
||||
"model.layers.74.input_layernorm",
|
||||
"model.layers.74.mlp.gate",
|
||||
"model.layers.74.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.74.post_attention_layernorm",
|
||||
"model.layers.74.self_attn.indexer.k_norm",
|
||||
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|
||||
"model.layers.74.self_attn.indexers_proj",
|
||||
"model.layers.74.self_attn.kv_a_layernorm",
|
||||
"model.layers.74.self_attn.q_a_layernorm",
|
||||
"model.layers.75.input_layernorm",
|
||||
"model.layers.75.mlp.gate",
|
||||
"model.layers.75.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.75.post_attention_layernorm",
|
||||
"model.layers.75.self_attn.indexer.k_norm",
|
||||
"model.layers.75.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.75.self_attn.indexers_proj",
|
||||
"model.layers.75.self_attn.kv_a_layernorm",
|
||||
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|
||||
"model.layers.76.input_layernorm",
|
||||
"model.layers.76.mlp.gate",
|
||||
"model.layers.76.mlp.gate.e_score_correction_bias",
|
||||
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|
||||
"model.layers.76.self_attn.indexer.k_norm",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.77.input_layernorm",
|
||||
"model.layers.77.mlp.gate",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.78.eh_proj",
|
||||
"model.layers.78.enorm",
|
||||
"model.layers.78.hnorm",
|
||||
"model.layers.78.input_layernorm",
|
||||
"model.layers.78.mlp.gate",
|
||||
"model.layers.78.mlp.gate.e_score_correction_bias",
|
||||
"model.layers.78.post_attention_layernorm",
|
||||
"model.layers.78.self_attn.indexer.k_norm",
|
||||
"model.layers.78.self_attn.indexer.k_norm.bias",
|
||||
"model.layers.78.self_attn.indexers_proj",
|
||||
"model.layers.78.self_attn.kv_a_layernorm",
|
||||
"model.layers.78.self_attn.q_a_layernorm",
|
||||
"model.layers.78.shared_head.norm",
|
||||
"model.norm"
|
||||
]
|
||||
}
|
||||
}
|
||||
1441793
trace_model_meta/ZhipuAI/GLM-5-FP8/tokenizer.json
Normal file
1441793
trace_model_meta/ZhipuAI/GLM-5-FP8/tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
33
trace_model_meta/ZhipuAI/GLM-5-FP8/tokenizer_config.json
Normal file
33
trace_model_meta/ZhipuAI/GLM-5-FP8/tokenizer_config.json
Normal file
@@ -0,0 +1,33 @@
|
||||
{
|
||||
"backend": "tokenizers",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"do_lower_case": false,
|
||||
"eos_token": "<|endoftext|>",
|
||||
"extra_special_tokens": [
|
||||
"<|endoftext|>",
|
||||
"[MASK]",
|
||||
"[gMASK]",
|
||||
"[sMASK]",
|
||||
"<sop>",
|
||||
"<eop>",
|
||||
"<|system|>",
|
||||
"<|user|>",
|
||||
"<|assistant|>",
|
||||
"<|observation|>",
|
||||
"<|begin_of_image|>",
|
||||
"<|end_of_image|>",
|
||||
"<|begin_of_video|>",
|
||||
"<|end_of_video|>",
|
||||
"<|begin_of_audio|>",
|
||||
"<|end_of_audio|>",
|
||||
"<|begin_of_transcription|>",
|
||||
"<|end_of_transcription|>"
|
||||
],
|
||||
"is_local": true,
|
||||
"model_max_length": 202752,
|
||||
"model_specific_special_tokens": {},
|
||||
"pad_token": "<|endoftext|>",
|
||||
"padding_side": "left",
|
||||
"remove_space": false,
|
||||
"tokenizer_class": "TokenizersBackend"
|
||||
}
|
||||
Reference in New Issue
Block a user