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  1. .gitattributes +1 -0
  2. README.md +39 -0
  3. chat_template.jinja +103 -0
  4. config.json +51 -0
  5. generation_config.json +10 -0
  6. model-00001-of-00090.safetensors +3 -0
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  49. special_tokens_map.json +40 -0
  50. tokenizer.json +3 -0
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,39 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ language:
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+ - en
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+ - zh
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+ library_name: mlx
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+ license: mit
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+ pipeline_tag: text-generation
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+ base_model: zai-org/GLM-4.5
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+ tags:
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+ - mlx
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+ ---
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+
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+ # sjug/GLM-4.5-MLX-9bit
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+
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+ This model [sjug/GLM-4.5-MLX-9bit](https://huggingface.co/sjug/GLM-4.5-MLX-9bit) was
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+ converted to MLX format from [zai-org/GLM-4.5](https://huggingface.co/zai-org/GLM-4.5)
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+ using mlx-lm version **0.26.3**.
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+
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+ ## Use with mlx
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+
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+ ```bash
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+ pip install mlx-lm
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+ ```
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+
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+ ```python
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+ from mlx_lm import load, generate
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+
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+ model, tokenizer = load("sjug/GLM-4.5-MLX-9bit")
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+
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+ prompt = "hello"
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+
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+ if tokenizer.chat_template is not None:
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+ messages = [{"role": "user", "content": prompt}]
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+ prompt = tokenizer.apply_chat_template(
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+ messages, add_generation_prompt=True
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+ )
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+
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+ response = generate(model, tokenizer, prompt=prompt, verbose=True)
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+ ```
chat_template.jinja ADDED
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1
+ [gMASK]<sop>
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+ {%- if tools -%}
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+ <|system|>
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+ # Tools
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+
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+ You may call one or more functions to assist with the user query.
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+
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+ You are provided with function signatures within <tools></tools> XML tags:
9
+ <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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+
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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}
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+ <arg_key>{arg-key-1}</arg_key>
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+ <arg_value>{arg-value-1}</arg_value>
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+ <arg_key>{arg-key-2}</arg_key>
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+ <arg_value>{arg-value-2}</arg_value>
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+ ...
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+ </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 -%}
34
+ {%- else -%}
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+ {{- content }}
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+ {%- endif -%}
37
+ {%- 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|>
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+ {{ visible_text(m.content) }}
47
+ {{- '/nothink' if (enable_thinking is defined and not enable_thinking and not visible_text(m.content).endswith("/nothink")) else '' -}}
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+ {%- elif m.role == 'assistant' -%}
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+ <|assistant|>
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+ {%- set reasoning_content = '' %}
51
+ {%- set content = visible_text(m.content) %}
52
+ {%- if m.reasoning_content is string %}
53
+ {%- set reasoning_content = m.reasoning_content %}
54
+ {%- else %}
55
+ {%- if '</think>' in content %}
56
+ {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
57
+ {%- set content = content.split('</think>')[-1].lstrip('\n') %}
58
+ {%- endif %}
59
+ {%- endif %}
60
+ {%- if loop.index0 > ns.last_user_index and reasoning_content -%}
61
+ {{ '\n<think>' + reasoning_content.strip() + '</think>'}}
62
+ {%- else -%}
63
+ {{ '\n<think></think>' }}
64
+ {%- endif -%}
65
+ {%- if content.strip() -%}
66
+ {{ '\n' + content.strip() }}
67
+ {%- endif -%}
68
+ {% if m.tool_calls %}
69
+ {% for tc in m.tool_calls %}
70
+ {%- if tc.function %}
71
+ {%- set tc = tc.function %}
72
+ {%- endif %}
73
+ {{ '\n<tool_call>' + tc.name }}
74
+ {% set _args = tc.arguments %}
75
+ {% for k, v in _args.items() %}
76
+ <arg_key>{{ k }}</arg_key>
77
+ <arg_value>{{ v | tojson(ensure_ascii=False) if v is not string else v }}</arg_value>
78
+ {% endfor %}
79
+ </tool_call>{% endfor %}
80
+ {% endif %}
81
+ {%- elif m.role == 'tool' -%}
82
+ {%- if m.content is string -%}
83
+ {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
84
+ {{- '<|observation|>' }}
85
+ {%- endif %}
86
+ {{- '\n<tool_response>\n' }}
87
+ {{- m.content }}
88
+ {{- '\n</tool_response>' }}
89
+ {%- else -%}
90
+ <|observation|>{% for tr in m.content %}
91
+
92
+ <tool_response>
93
+ {{ tr.output if tr.output is defined else tr }}
94
+ </tool_response>{% endfor -%}
95
+ {% endif -%}
96
+ {%- elif m.role == 'system' -%}
97
+ <|system|>
98
+ {{ visible_text(m.content) }}
99
+ {%- endif -%}
100
+ {%- endfor -%}
101
+ {%- if add_generation_prompt -%}
102
+ <|assistant|>{{- '\n<think></think>' if (enable_thinking is defined and not enable_thinking) else '' -}}
103
+ {%- endif -%}
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+ {
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+ "architectures": [
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+ "Glm4MoeForCausalLM"
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+ ],
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+ "attention_bias": true,
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+ "attention_dropout": 0.0,
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+ "eos_token_id": [
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+ 151329,
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+ ],
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+ "first_k_dense_replace": 3,
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+ "head_dim": 128,
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+ "hidden_act": "silu",
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+ "hidden_size": 5120,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 12288,
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+ "max_position_embeddings": 131072,
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+ "model_type": "glm4_moe",
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+ "moe_intermediate_size": 1536,
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+ "n_group": 1,
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+ "n_routed_experts": 160,
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+ "n_shared_experts": 1,
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+ "norm_topk_prob": true,
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+ "num_attention_heads": 96,
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+ "num_experts_per_tok": 8,
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+ "num_hidden_layers": 92,
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+ "num_key_value_heads": 8,
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+ "num_nextn_predict_layers": 1,
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+ "pad_token_id": 151329,
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+ "partial_rotary_factor": 0.5,
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+ "quantization": {
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+ "group_size": 32,
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+ "bits": 8
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+ },
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+ "quantization_config": {
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+ "group_size": 32,
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+ "bits": 8
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+ },
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+ "rms_norm_eps": 1e-05,
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+ "rope_scaling": null,
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+ "rope_theta": 1000000,
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+ "routed_scaling_factor": 2.5,
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+ "tie_word_embeddings": false,
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+ "topk_group": 1,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.54.0",
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+ "use_cache": true,
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+ "use_qk_norm": true,
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+ "vocab_size": 151552
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+ }
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