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.gitattributes CHANGED
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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 CHANGED
@@ -1,3 +1,197 @@
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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ tags:
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+ - unsloth
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+ base_model:
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+ - Qwen/Qwen3-30B-A3B-Instruct-2507-FP8
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+ library_name: transformers
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+ license: apache-2.0
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+ license_link: https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507/blob/main/LICENSE
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+ pipeline_tag: text-generation
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+ ---
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+ > [!NOTE]
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+ > Includes Unsloth **chat template fixes**! <br> For `llama.cpp`, use `--jinja`
13
+ >
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+
15
+ <div>
16
+ <p style="margin-top: 0;margin-bottom: 0;">
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+ <em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em>
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+ </p>
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+ <div style="display: flex; gap: 5px; align-items: center; ">
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+ <a href="https://github.com/unslothai/unsloth/">
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+ <img src="https://github.com/unslothai/unsloth/raw/main/images/unsloth%20new%20logo.png" width="133">
22
+ </a>
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+ <a href="https://discord.gg/unsloth">
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+ <img src="https://github.com/unslothai/unsloth/raw/main/images/Discord%20button.png" width="173">
25
+ </a>
26
+ <a href="https://docs.unsloth.ai/">
27
+ <img src="https://raw.githubusercontent.com/unslothai/unsloth/refs/heads/main/images/documentation%20green%20button.png" width="143">
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+ </a>
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+ </div>
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+ </div>
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+
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+
33
+ # Qwen3-30B-A3B-Instruct-2507-FP8
34
+ <a href="https://chat.qwen.ai/" target="_blank" style="margin: 2px;">
35
+ <img alt="Chat" src="https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5" style="display: inline-block; vertical-align: middle;"/>
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+ </a>
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+
38
+ ## Highlights
39
+
40
+ We introduce the updated version of the **Qwen3-30B-A3B non-thinking mode**, named **Qwen3-30B-A3B-Instruct-2507-FP8**, featuring the following key enhancements:
41
+
42
+ - **Significant improvements** in general capabilities, including **instruction following, logical reasoning, text comprehension, mathematics, science, coding and tool usage**.
43
+ - **Substantial gains** in long-tail knowledge coverage across **multiple languages**.
44
+ - **Markedly better alignment** with user preferences in **subjective and open-ended tasks**, enabling more helpful responses and higher-quality text generation.
45
+ - **Enhanced capabilities** in **256K long-context understanding**.
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+
47
+ ## Model Overview
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+
49
+ **Qwen3-30B-A3B-Instruct-2507-FP8** has the following features:
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+ - Type: Causal Language Models
51
+ - Training Stage: Pretraining & Post-training
52
+ - Number of Parameters: 30.5B in total and 3.3B activated
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+ - Number of Paramaters (Non-Embedding): 29.9B
54
+ - Number of Layers: 48
55
+ - Number of Attention Heads (GQA): 32 for Q and 4 for KV
56
+ - Number of Experts: 128
57
+ - Number of Activated Experts: 8
58
+ - Context Length: **262,144 natively**.
59
+
60
+ **NOTE: This model supports only non-thinking mode and does not generate ``<think></think>`` blocks in its output. Meanwhile, specifying `enable_thinking=False` is no longer required.**
61
+
62
+ For more details, including benchmark evaluation, hardware requirements, and inference performance, please refer to our [blog](https://qwenlm.github.io/blog/qwen3/), [GitHub](https://github.com/QwenLM/Qwen3), and [Documentation](https://qwen.readthedocs.io/en/latest/).
63
+
64
+
65
+ ## Quickstart
66
+
67
+ The code of Qwen3-MoE has been in the latest Hugging Face `transformers` and we advise you to use the latest version of `transformers`.
68
+
69
+ With `transformers<4.51.0`, you will encounter the following error:
70
+ ```
71
+ KeyError: 'qwen3_moe'
72
+ ```
73
+
74
+ The following contains a code snippet illustrating how to use the model generate content based on given inputs.
75
+ ```python
76
+ from transformers import AutoModelForCausalLM, AutoTokenizer
77
+
78
+ model_name = "Qwen/Qwen3-30B-A3B-Instruct-2507-FP8"
79
+
80
+ # load the tokenizer and the model
81
+ tokenizer = AutoTokenizer.from_pretrained(model_name)
82
+ model = AutoModelForCausalLM.from_pretrained(
83
+ model_name,
84
+ torch_dtype="auto",
85
+ device_map="auto"
86
+ )
87
+
88
+ # prepare the model input
89
+ prompt = "Give me a short introduction to large language model."
90
+ messages = [
91
+ {"role": "user", "content": prompt}
92
+ ]
93
+ text = tokenizer.apply_chat_template(
94
+ messages,
95
+ tokenize=False,
96
+ add_generation_prompt=True,
97
+ )
98
+ model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
99
+
100
+ # conduct text completion
101
+ generated_ids = model.generate(
102
+ **model_inputs,
103
+ max_new_tokens=16384
104
+ )
105
+ output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()
106
+
107
+ content = tokenizer.decode(output_ids, skip_special_tokens=True)
108
+
109
+ print("content:", content)
110
+ ```
111
+
112
+ For deployment, you can use `sglang>=0.4.6.post1` or `vllm>=0.8.5` or to create an OpenAI-compatible API endpoint:
113
+ - SGLang:
114
+ ```shell
115
+ python -m sglang.launch_server --model-path Qwen/Qwen3-30B-A3B-Instruct-2507 --tp 8 --context-length 262144
116
+ ```
117
+ - vLLM:
118
+ ```shell
119
+ vllm serve Qwen/Qwen3-30B-A3B-Instruct-2507 --tensor-parallel-size 8 --max-model-len 262144
120
+ ```
121
+
122
+ **Note: If you encounter out-of-memory (OOM) issues, consider reducing the context length to a shorter value, such as `32,768`.**
123
+
124
+ For local use, applications such as Ollama, LMStudio, MLX-LM, llama.cpp, and KTransformers have also supported Qwen3.
125
+
126
+ ## Agentic Use
127
+
128
+ Qwen3 excels in tool calling capabilities. We recommend using [Qwen-Agent](https://github.com/QwenLM/Qwen-Agent) to make the best use of agentic ability of Qwen3. Qwen-Agent encapsulates tool-calling templates and tool-calling parsers internally, greatly reducing coding complexity.
129
+
130
+ To define the available tools, you can use the MCP configuration file, use the integrated tool of Qwen-Agent, or integrate other tools by yourself.
131
+ ```python
132
+ from qwen_agent.agents import Assistant
133
+
134
+ # Define LLM
135
+ llm_cfg = {
136
+ 'model': 'Qwen3-30B-A3B-Instruct-2507-FP8',
137
+
138
+ # Use a custom endpoint compatible with OpenAI API:
139
+ 'model_server': 'http://localhost:8000/v1', # api_base
140
+ 'api_key': 'EMPTY',
141
+ }
142
+
143
+ # Define Tools
144
+ tools = [
145
+ {'mcpServers': { # You can specify the MCP configuration file
146
+ 'time': {
147
+ 'command': 'uvx',
148
+ 'args': ['mcp-server-time', '--local-timezone=Asia/Shanghai']
149
+ },
150
+ "fetch": {
151
+ "command": "uvx",
152
+ "args": ["mcp-server-fetch"]
153
+ }
154
+ }
155
+ },
156
+ 'code_interpreter', # Built-in tools
157
+ ]
158
+
159
+ # Define Agent
160
+ bot = Assistant(llm=llm_cfg, function_list=tools)
161
+
162
+ # Streaming generation
163
+ messages = [{'role': 'user', 'content': 'https://qwenlm.github.io/blog/ Introduce the latest developments of Qwen'}]
164
+ for responses in bot.run(messages=messages):
165
+ pass
166
+ print(responses)
167
+ ```
168
+
169
+ ## Best Practices
170
+
171
+ To achieve optimal performance, we recommend the following settings:
172
+
173
+ 1. **Sampling Parameters**:
174
+ - We suggest using `Temperature=0.7`, `TopP=0.8`, `TopK=20`, and `MinP=0`.
175
+ - For supported frameworks, you can adjust the `presence_penalty` parameter between 0 and 2 to reduce endless repetitions. However, using a higher value may occasionally result in language mixing and a slight decrease in model performance.
176
+
177
+ 2. **Adequate Output Length**: We recommend using an output length of 16,384 tokens for most queries, which is adequate for instruct models.
178
+
179
+ 3. **Standardize Output Format**: We recommend using prompts to standardize model outputs when benchmarking.
180
+ - **Math Problems**: Include "Please reason step by step, and put your final answer within \boxed{}." in the prompt.
181
+ - **Multiple-Choice Questions**: Add the following JSON structure to the prompt to standardize responses: "Please show your choice in the `answer` field with only the choice letter, e.g., `"answer": "C"`."
182
+
183
+ ### Citation
184
+
185
+ If you find our work helpful, feel free to give us a cite.
186
+
187
+ ```
188
+ @misc{qwen3technicalreport,
189
+ title={Qwen3 Technical Report},
190
+ author={Qwen Team},
191
+ year={2025},
192
+ eprint={2505.09388},
193
+ archivePrefix={arXiv},
194
+ primaryClass={cs.CL},
195
+ url={https://arxiv.org/abs/2505.09388},
196
+ }
197
+ ```
added_tokens.json ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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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_call>": 151657,
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+ "<tool_response>": 151665,
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+ "<|box_end|>": 151649,
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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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+ "<|fim_suffix|>": 151661,
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+ "<|im_end|>": 151645,
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+ "<|im_start|>": 151644,
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+ "<|image_pad|>": 151655,
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+ "<|object_ref_end|>": 151647,
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+ "<|object_ref_start|>": 151646,
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+ "<|quad_end|>": 151651,
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+ "<|quad_start|>": 151650,
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+ "<|repo_name|>": 151663,
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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
@@ -0,0 +1,89 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
3
+ {%- if messages[0].role == 'system' %}
4
+ {{- messages[0].content + '\n\n' }}
5
+ {%- endif %}
6
+ {{- "# 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>" }}
7
+ {%- for tool in tools %}
8
+ {{- "\n" }}
9
+ {{- tool | tojson }}
10
+ {%- endfor %}
11
+ {{- "\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" }}
12
+ {%- else %}
13
+ {%- if messages[0].role == 'system' %}
14
+ {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
15
+ {%- endif %}
16
+ {%- endif %}
17
+ {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
18
+ {%- for message in messages[::-1] %}
19
+ {%- set index = (messages|length - 1) - loop.index0 %}
20
+ {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
21
+ {%- set ns.multi_step_tool = false %}
22
+ {%- set ns.last_query_index = index %}
23
+ {%- endif %}
24
+ {%- endfor %}
25
+ {%- for message in messages %}
26
+ {%- if message.content is string %}
27
+ {%- set content = message.content %}
28
+ {%- else %}
29
+ {%- set content = '' %}
30
+ {%- endif %}
31
+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
32
+ {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
33
+ {%- elif message.role == "assistant" %}
34
+ {%- set reasoning_content = '' %}
35
+ {%- if message.reasoning_content is string %}
36
+ {%- set reasoning_content = message.reasoning_content %}
37
+ {%- else %}
38
+ {%- if '</think>' in content %}
39
+ {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
40
+ {%- set content = content.split('</think>')[-1].lstrip('\n') %}
41
+ {%- endif %}
42
+ {%- endif %}
43
+ {%- if loop.index0 > ns.last_query_index %}
44
+ {%- if loop.last or (not loop.last and reasoning_content) %}
45
+ {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
46
+ {%- else %}
47
+ {{- '<|im_start|>' + message.role + '\n' + content }}
48
+ {%- endif %}
49
+ {%- else %}
50
+ {{- '<|im_start|>' + message.role + '\n' + content }}
51
+ {%- endif %}
52
+ {%- if message.tool_calls %}
53
+ {%- for tool_call in message.tool_calls %}
54
+ {%- if (loop.first and content) or (not loop.first) %}
55
+ {{- '\n' }}
56
+ {%- endif %}
57
+ {%- if tool_call.function %}
58
+ {%- set tool_call = tool_call.function %}
59
+ {%- endif %}
60
+ {{- '<tool_call>\n{"name": "' }}
61
+ {{- tool_call.name }}
62
+ {{- '", "arguments": ' }}
63
+ {%- if tool_call.arguments is string %}
64
+ {{- tool_call.arguments }}
65
+ {%- else %}
66
+ {{- tool_call.arguments | tojson }}
67
+ {%- endif %}
68
+ {{- '}\n</tool_call>' }}
69
+ {%- endfor %}
70
+ {%- endif %}
71
+ {{- '<|im_end|>\n' }}
72
+ {%- elif message.role == "tool" %}
73
+ {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
74
+ {{- '<|im_start|>user' }}
75
+ {%- endif %}
76
+ {{- '\n<tool_response>\n' }}
77
+ {{- content }}
78
+ {{- '\n</tool_response>' }}
79
+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
80
+ {{- '<|im_end|>\n' }}
81
+ {%- endif %}
82
+ {%- endif %}
83
+ {%- endfor %}
84
+ {%- if add_generation_prompt %}
85
+ {{- '<|im_start|>assistant\n' }}
86
+ {%- if enable_thinking is defined and enable_thinking is false %}
87
+ {{- '<think>\n\n</think>\n\n' }}
88
+ {%- endif %}
89
+ {%- endif %}
config.json ADDED
@@ -0,0 +1,195 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architectures": [
3
+ "Qwen3MoeForCausalLM"
4
+ ],
5
+ "attention_bias": false,
6
+ "attention_dropout": 0.0,
7
+ "decoder_sparse_step": 1,
8
+ "eos_token_id": 151645,
9
+ "head_dim": 128,
10
+ "hidden_act": "silu",
11
+ "hidden_size": 2048,
12
+ "initializer_range": 0.02,
13
+ "intermediate_size": 6144,
14
+ "max_position_embeddings": 262144,
15
+ "max_window_layers": 48,
16
+ "mlp_only_layers": [],
17
+ "model_type": "qwen3_moe",
18
+ "moe_intermediate_size": 768,
19
+ "norm_topk_prob": true,
20
+ "num_attention_heads": 32,
21
+ "num_experts": 128,
22
+ "num_experts_per_tok": 8,
23
+ "num_hidden_layers": 48,
24
+ "num_key_value_heads": 4,
25
+ "output_router_logits": false,
26
+ "pad_token_id": 151654,
27
+ "quantization_config": {
28
+ "activation_scheme": "dynamic",
29
+ "fmt": "e4m3",
30
+ "modules_to_not_convert": [
31
+ "lm_head",
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+ "model.layers.0.input_layernorm",
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+ "model.layers.0.mlp.gate",
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+ "model.layers.0.post_attention_layernorm",
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241
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