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.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.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 +1,111 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ pipeline_tag: text-generation
4
+ inference: true
5
+ widget:
6
+ - text: Hello!
7
+ example_title: Hello world
8
+ group: Python
9
+ ---
10
+
11
+ This tiny model is for debugging. It is randomly initialized with the config adapted from [Qwen/Qwen3-235B-A22B](https://huggingface.co/Qwen/Qwen3-235B-A22B).
12
+
13
+ ### Example usage:
14
+
15
+ ```python
16
+ from transformers import pipeline
17
+ model_id = "tiny-random/qwen3-moe"
18
+ pipe = pipeline(
19
+ "text-generation", model=model_id, device="cuda",
20
+ trust_remote_code=True, max_new_tokens=3,
21
+ )
22
+ print(pipe("Hello World!"))
23
+
24
+ from transformers import AutoModelForCausalLM, AutoTokenizer
25
+ tokenizer = AutoTokenizer.from_pretrained(model_id)
26
+ model = AutoModelForCausalLM.from_pretrained(
27
+ model_id,
28
+ torch_dtype="auto",
29
+ device_map="auto"
30
+ )
31
+ prompt = "Give me a short introduction to large language model."
32
+ messages = [
33
+ {"role": "user", "content": prompt}
34
+ ]
35
+ text = tokenizer.apply_chat_template(
36
+ messages,
37
+ tokenize=False,
38
+ add_generation_prompt=True,
39
+ enable_thinking=True # Switches between thinking and non-thinking modes. Default is True.
40
+ )
41
+ print(text)
42
+ model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
43
+ generated_ids = model.generate(
44
+ **model_inputs,
45
+ max_new_tokens=128
46
+ )
47
+ output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()
48
+ try:
49
+ # rindex finding 151668 (</think>)
50
+ index = len(output_ids) - output_ids[::-1].index(151668)
51
+ except ValueError:
52
+ index = 0
53
+ thinking_content = tokenizer.decode(output_ids[:index], skip_special_tokens=True).strip("\n")
54
+ content = tokenizer.decode(output_ids[index:], skip_special_tokens=True).strip("\n")
55
+ print("thinking content:", thinking_content)
56
+ print("content:", content)
57
+ ```
58
+
59
+ ### Codes to create this repo:
60
+
61
+ ```python
62
+ import torch
63
+
64
+ from transformers import (
65
+ AutoConfig,
66
+ AutoModelForCausalLM,
67
+ AutoTokenizer,
68
+ GenerationConfig,
69
+ pipeline,
70
+ set_seed,
71
+ )
72
+
73
+ source_model_id = "Qwen/Qwen3-235B-A22B"
74
+ save_folder = "/tmp/tiny-random/qwen3-moe"
75
+
76
+ tokenizer = AutoTokenizer.from_pretrained(
77
+ source_model_id, trust_remote_code=True,
78
+ )
79
+ tokenizer.save_pretrained(save_folder)
80
+
81
+ config = AutoConfig.from_pretrained(
82
+ source_model_id, trust_remote_code=True,
83
+ )
84
+ config._name_or_path = source_model_id
85
+ config.hidden_size = 64
86
+ config.intermediate_size = 128
87
+ config.moe_intermediate_size = 128
88
+ config.head_dim = 32
89
+ config.decoder_sparse_step = 2 # layer0=mlp, layer1=moe
90
+ config.num_experts = 8
91
+ config.num_experts_per_tok = 2
92
+ config.num_key_value_heads = 1
93
+ config.num_attention_heads = 2
94
+ config.num_hidden_layers = 2
95
+ config.max_window_layers = 1
96
+ config.tie_word_embeddings = True
97
+ model = AutoModelForCausalLM.from_config(
98
+ config,
99
+ torch_dtype=torch.bfloat16,
100
+ trust_remote_code=True,
101
+ )
102
+ model.generation_config = GenerationConfig.from_pretrained(
103
+ source_model_id, trust_remote_code=True,
104
+ )
105
+ set_seed(42)
106
+ with torch.no_grad():
107
+ for name, p in sorted(model.named_parameters()):
108
+ torch.nn.init.normal_(p, 0, 0.5)
109
+ print(name, p.shape)
110
+ model.save_pretrained(save_folder)
111
+ ```
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+ "</think>": 151668,
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+ "</tool_call>": 151658,
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+ "</tool_response>": 151666,
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+ "<think>": 151667,
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+ "<tool_response>": 151665,
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+ "<|box_start|>": 151648,
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+ "<|endoftext|>": 151643,
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+ "<|file_sep|>": 151664,
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+ "<|fim_middle|>": 151660,
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+ "<|fim_pad|>": 151662,
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+ "<|fim_prefix|>": 151659,
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+ "<|im_end|>": 151645,
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+ "<|object_ref_end|>": 151647,
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+ "<|video_pad|>": 151656,
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+ "<|vision_end|>": 151653,
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+ "<|vision_pad|>": 151654,
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+ "<|vision_start|>": 151652
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+ }
chat_template.jinja ADDED
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+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
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+ {%- if messages[0].role == 'system' %}
4
+ {{- messages[0].content + '\n\n' }}
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+ {%- endif %}
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+ {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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+ {%- for tool in tools %}
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+ {{- "\n" }}
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+ {{- tool | tojson }}
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+ {%- endfor %}
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+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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+ {%- else %}
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+ {%- if messages[0].role == 'system' %}
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+ {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
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+ {%- endif %}
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+ {%- endif %}
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+ {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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+ {%- for message in messages[::-1] %}
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+ {%- set index = (messages|length - 1) - loop.index0 %}
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+ {%- if ns.multi_step_tool and message.role == "user" and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
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+ {%- set ns.multi_step_tool = false %}
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+ {%- set ns.last_query_index = index %}
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+ {%- endif %}
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+ {%- endfor %}
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+ {%- for message in messages %}
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+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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+ {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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+ {%- elif message.role == "assistant" %}
29
+ {%- set content = message.content %}
30
+ {%- set reasoning_content = '' %}
31
+ {%- if message.reasoning_content is defined and message.reasoning_content is not none %}
32
+ {%- set reasoning_content = message.reasoning_content %}
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+ {%- else %}
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+ {%- if '</think>' in message.content %}
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+ {%- set content = message.content.split('</think>')[-1].lstrip('\n') %}
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+ {%- set reasoning_content = message.content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
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+ {%- endif %}
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+ {%- endif %}
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+ {%- if loop.index0 > ns.last_query_index %}
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+ {%- if loop.last or (not loop.last and reasoning_content) %}
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+ {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
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+ {%- else %}
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+ {{- '<|im_start|>' + message.role + '\n' + content }}
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+ {%- endif %}
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+ {%- else %}
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+ {{- '<|im_start|>' + message.role + '\n' + content }}
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+ {%- if message.tool_calls %}
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+ {%- for tool_call in message.tool_calls %}
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+ {%- if (loop.first and content) or (not loop.first) %}
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+ {%- endif %}
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+ {{- '<tool_call>\n{"name": "' }}
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+ {{- tool_call.name }}
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+ {{- '", "arguments": ' }}
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+ {%- if tool_call.arguments is string %}
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+ {{- tool_call.arguments }}
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+ {%- else %}
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+ {{- tool_call.arguments | tojson }}
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+ {%- endif %}
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+ {{- '}\n</tool_call>' }}
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+ {%- endfor %}
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+ {%- endif %}
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+ {{- '<|im_end|>\n' }}
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+ {%- elif message.role == "tool" %}
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+ {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
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+ {{- '<|im_start|>user' }}
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+ {%- endif %}
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+ {{- '\n<tool_response>\n' }}
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+ {{- message.content }}
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+ {{- '\n</tool_response>' }}
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+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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+ {{- '<|im_end|>\n' }}
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+ {%- endif %}
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+ {%- endfor %}
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+ {%- if add_generation_prompt %}
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+ {{- '<|im_start|>assistant\n' }}
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+ {%- if enable_thinking is defined and enable_thinking is false %}
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+ {{- '<think>\n\n</think>\n\n' }}
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+ "content": "</tool_response>",
191
+ "lstrip": false,
192
+ "normalized": false,
193
+ "rstrip": false,
194
+ "single_word": false,
195
+ "special": false
196
+ },
197
+ "151667": {
198
+ "content": "<think>",
199
+ "lstrip": false,
200
+ "normalized": false,
201
+ "rstrip": false,
202
+ "single_word": false,
203
+ "special": false
204
+ },
205
+ "151668": {
206
+ "content": "</think>",
207
+ "lstrip": false,
208
+ "normalized": false,
209
+ "rstrip": false,
210
+ "single_word": false,
211
+ "special": false
212
+ }
213
+ },
214
+ "additional_special_tokens": [
215
+ "<|im_start|>",
216
+ "<|im_end|>",
217
+ "<|object_ref_start|>",
218
+ "<|object_ref_end|>",
219
+ "<|box_start|>",
220
+ "<|box_end|>",
221
+ "<|quad_start|>",
222
+ "<|quad_end|>",
223
+ "<|vision_start|>",
224
+ "<|vision_end|>",
225
+ "<|vision_pad|>",
226
+ "<|image_pad|>",
227
+ "<|video_pad|>"
228
+ ],
229
+ "bos_token": null,
230
+ "clean_up_tokenization_spaces": false,
231
+ "eos_token": "<|im_end|>",
232
+ "errors": "replace",
233
+ "extra_special_tokens": {},
234
+ "model_max_length": 131072,
235
+ "pad_token": "<|endoftext|>",
236
+ "split_special_tokens": false,
237
+ "tokenizer_class": "Qwen2Tokenizer",
238
+ "unk_token": null
239
+ }
vocab.json ADDED
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