Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- README.md +197 -3
- added_tokens.json +28 -0
- chat_template.jinja +89 -0
- config.json +195 -0
- generation_config.json +6 -0
- merges.txt +0 -0
- model-00001-of-00004.safetensors +3 -0
- model-00002-of-00004.safetensors +3 -0
- model-00003-of-00004.safetensors +3 -0
- model-00004-of-00004.safetensors +3 -0
- model.safetensors.index.json +0 -0
- special_tokens_map.json +31 -0
- tokenizer.json +3 -0
- tokenizer_config.json +241 -0
- vocab.json +0 -0
.gitattributes
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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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*.zip 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
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README.md
CHANGED
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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`
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>
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<div>
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<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">
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</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">
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</a>
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<a href="https://docs.unsloth.ai/">
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<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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# Qwen3-30B-A3B-Instruct-2507-FP8
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<a href="https://chat.qwen.ai/" target="_blank" style="margin: 2px;">
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<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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+
|
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## Highlights
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|
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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:
|
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+
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+
- **Significant improvements** in general capabilities, including **instruction following, logical reasoning, text comprehension, mathematics, science, coding and tool usage**.
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43 |
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- **Substantial gains** in long-tail knowledge coverage across **multiple languages**.
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- **Markedly better alignment** with user preferences in **subjective and open-ended tasks**, enabling more helpful responses and higher-quality text generation.
|
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+
- **Enhanced capabilities** in **256K long-context understanding**.
|
46 |
+
|
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+
## Model Overview
|
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+
|
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+
**Qwen3-30B-A3B-Instruct-2507-FP8** has the following features:
|
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+
- Type: Causal Language Models
|
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+
- Training Stage: Pretraining & Post-training
|
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+
- Number of Parameters: 30.5B in total and 3.3B activated
|
53 |
+
- 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 |
+
```
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73 |
+
|
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+
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
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77 |
+
|
78 |
+
model_name = "Qwen/Qwen3-30B-A3B-Instruct-2507-FP8"
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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",
|
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+
device_map="auto"
|
86 |
+
)
|
87 |
+
|
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+
# prepare the model input
|
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+
prompt = "Give me a short introduction to large language model."
|
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+
messages = [
|
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{"role": "user", "content": prompt}
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]
|
93 |
+
text = tokenizer.apply_chat_template(
|
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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 |
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generated_ids = model.generate(
|
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**model_inputs,
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max_new_tokens=16384
|
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)
|
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output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()
|
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+
|
107 |
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content = tokenizer.decode(output_ids, skip_special_tokens=True)
|
108 |
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|
109 |
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print("content:", content)
|
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```
|
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+
|
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 |
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python -m sglang.launch_server --model-path Qwen/Qwen3-30B-A3B-Instruct-2507 --tp 8 --context-length 262144
|
116 |
+
```
|
117 |
+
- vLLM:
|
118 |
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```shell
|
119 |
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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 |
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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 |
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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 |
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"command": "uvx",
|
152 |
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"args": ["mcp-server-fetch"]
|
153 |
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}
|
154 |
+
}
|
155 |
+
},
|
156 |
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'code_interpreter', # Built-in tools
|
157 |
+
]
|
158 |
+
|
159 |
+
# Define Agent
|
160 |
+
bot = Assistant(llm=llm_cfg, function_list=tools)
|
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+
|
162 |
+
# Streaming generation
|
163 |
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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 |
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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 |
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title={Qwen3 Technical Report},
|
190 |
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author={Qwen Team},
|
191 |
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year={2025},
|
192 |
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eprint={2505.09388},
|
193 |
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archivePrefix={arXiv},
|
194 |
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primaryClass={cs.CL},
|
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url={https://arxiv.org/abs/2505.09388},
|
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}
|
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```
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added_tokens.json
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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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}
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chat_template.jinja
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{%- if tools %}
|
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{{- '<|im_start|>system\n' }}
|
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{%- if messages[0].role == 'system' %}
|
4 |
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{{- messages[0].content + '\n\n' }}
|
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{%- 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 |
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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 %}
|
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 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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",
|
32 |
+
"model.layers.0.input_layernorm",
|
33 |
+
"model.layers.0.mlp.gate",
|
34 |
+
"model.layers.0.post_attention_layernorm",
|
35 |
+
"model.layers.1.input_layernorm",
|
36 |
+
"model.layers.1.mlp.gate",
|
37 |
+
"model.layers.1.post_attention_layernorm",
|
38 |
+
"model.layers.2.input_layernorm",
|
39 |
+
"model.layers.2.mlp.gate",
|
40 |
+
"model.layers.2.post_attention_layernorm",
|
41 |
+
"model.layers.3.input_layernorm",
|
42 |
+
"model.layers.3.mlp.gate",
|
43 |
+
"model.layers.3.post_attention_layernorm",
|
44 |
+
"model.layers.4.input_layernorm",
|
45 |
+
"model.layers.4.mlp.gate",
|
46 |
+
"model.layers.4.post_attention_layernorm",
|
47 |
+
"model.layers.5.input_layernorm",
|
48 |
+
"model.layers.5.mlp.gate",
|
49 |
+
"model.layers.5.post_attention_layernorm",
|
50 |
+
"model.layers.6.input_layernorm",
|
51 |
+
"model.layers.6.mlp.gate",
|
52 |
+
"model.layers.6.post_attention_layernorm",
|
53 |
+
"model.layers.7.input_layernorm",
|
54 |
+
"model.layers.7.mlp.gate",
|
55 |
+
"model.layers.7.post_attention_layernorm",
|
56 |
+
"model.layers.8.input_layernorm",
|
57 |
+
"model.layers.8.mlp.gate",
|
58 |
+
"model.layers.8.post_attention_layernorm",
|
59 |
+
"model.layers.9.input_layernorm",
|
60 |
+
"model.layers.9.mlp.gate",
|
61 |
+
"model.layers.9.post_attention_layernorm",
|
62 |
+
"model.layers.10.input_layernorm",
|
63 |
+
"model.layers.10.mlp.gate",
|
64 |
+
"model.layers.10.post_attention_layernorm",
|
65 |
+
"model.layers.11.input_layernorm",
|
66 |
+
"model.layers.11.mlp.gate",
|
67 |
+
"model.layers.11.post_attention_layernorm",
|
68 |
+
"model.layers.12.input_layernorm",
|
69 |
+
"model.layers.12.mlp.gate",
|
70 |
+
"model.layers.12.post_attention_layernorm",
|
71 |
+
"model.layers.13.input_layernorm",
|
72 |
+
"model.layers.13.mlp.gate",
|
73 |
+
"model.layers.13.post_attention_layernorm",
|
74 |
+
"model.layers.14.input_layernorm",
|
75 |
+
"model.layers.14.mlp.gate",
|
76 |
+
"model.layers.14.post_attention_layernorm",
|
77 |
+
"model.layers.15.input_layernorm",
|
78 |
+
"model.layers.15.mlp.gate",
|
79 |
+
"model.layers.15.post_attention_layernorm",
|
80 |
+
"model.layers.16.input_layernorm",
|
81 |
+
"model.layers.16.mlp.gate",
|
82 |
+
"model.layers.16.post_attention_layernorm",
|
83 |
+
"model.layers.17.input_layernorm",
|
84 |
+
"model.layers.17.mlp.gate",
|
85 |
+
"model.layers.17.post_attention_layernorm",
|
86 |
+
"model.layers.18.input_layernorm",
|
87 |
+
"model.layers.18.mlp.gate",
|
88 |
+
"model.layers.18.post_attention_layernorm",
|
89 |
+
"model.layers.19.input_layernorm",
|
90 |
+
"model.layers.19.mlp.gate",
|
91 |
+
"model.layers.19.post_attention_layernorm",
|
92 |
+
"model.layers.20.input_layernorm",
|
93 |
+
"model.layers.20.mlp.gate",
|
94 |
+
"model.layers.20.post_attention_layernorm",
|
95 |
+
"model.layers.21.input_layernorm",
|
96 |
+
"model.layers.21.mlp.gate",
|
97 |
+
"model.layers.21.post_attention_layernorm",
|
98 |
+
"model.layers.22.input_layernorm",
|
99 |
+
"model.layers.22.mlp.gate",
|
100 |
+
"model.layers.22.post_attention_layernorm",
|
101 |
+
"model.layers.23.input_layernorm",
|
102 |
+
"model.layers.23.mlp.gate",
|
103 |
+
"model.layers.23.post_attention_layernorm",
|
104 |
+
"model.layers.24.input_layernorm",
|
105 |
+
"model.layers.24.mlp.gate",
|
106 |
+
"model.layers.24.post_attention_layernorm",
|
107 |
+
"model.layers.25.input_layernorm",
|
108 |
+
"model.layers.25.mlp.gate",
|
109 |
+
"model.layers.25.post_attention_layernorm",
|
110 |
+
"model.layers.26.input_layernorm",
|
111 |
+
"model.layers.26.mlp.gate",
|
112 |
+
"model.layers.26.post_attention_layernorm",
|
113 |
+
"model.layers.27.input_layernorm",
|
114 |
+
"model.layers.27.mlp.gate",
|
115 |
+
"model.layers.27.post_attention_layernorm",
|
116 |
+
"model.layers.28.input_layernorm",
|
117 |
+
"model.layers.28.mlp.gate",
|
118 |
+
"model.layers.28.post_attention_layernorm",
|
119 |
+
"model.layers.29.input_layernorm",
|
120 |
+
"model.layers.29.mlp.gate",
|
121 |
+
"model.layers.29.post_attention_layernorm",
|
122 |
+
"model.layers.30.input_layernorm",
|
123 |
+
"model.layers.30.mlp.gate",
|
124 |
+
"model.layers.30.post_attention_layernorm",
|
125 |
+
"model.layers.31.input_layernorm",
|
126 |
+
"model.layers.31.mlp.gate",
|
127 |
+
"model.layers.31.post_attention_layernorm",
|
128 |
+
"model.layers.32.input_layernorm",
|
129 |
+
"model.layers.32.mlp.gate",
|
130 |
+
"model.layers.32.post_attention_layernorm",
|
131 |
+
"model.layers.33.input_layernorm",
|
132 |
+
"model.layers.33.mlp.gate",
|
133 |
+
"model.layers.33.post_attention_layernorm",
|
134 |
+
"model.layers.34.input_layernorm",
|
135 |
+
"model.layers.34.mlp.gate",
|
136 |
+
"model.layers.34.post_attention_layernorm",
|
137 |
+
"model.layers.35.input_layernorm",
|
138 |
+
"model.layers.35.mlp.gate",
|
139 |
+
"model.layers.35.post_attention_layernorm",
|
140 |
+
"model.layers.36.input_layernorm",
|
141 |
+
"model.layers.36.mlp.gate",
|
142 |
+
"model.layers.36.post_attention_layernorm",
|
143 |
+
"model.layers.37.input_layernorm",
|
144 |
+
"model.layers.37.mlp.gate",
|
145 |
+
"model.layers.37.post_attention_layernorm",
|
146 |
+
"model.layers.38.input_layernorm",
|
147 |
+
"model.layers.38.mlp.gate",
|
148 |
+
"model.layers.38.post_attention_layernorm",
|
149 |
+
"model.layers.39.input_layernorm",
|
150 |
+
"model.layers.39.mlp.gate",
|
151 |
+
"model.layers.39.post_attention_layernorm",
|
152 |
+
"model.layers.40.input_layernorm",
|
153 |
+
"model.layers.40.mlp.gate",
|
154 |
+
"model.layers.40.post_attention_layernorm",
|
155 |
+
"model.layers.41.input_layernorm",
|
156 |
+
"model.layers.41.mlp.gate",
|
157 |
+
"model.layers.41.post_attention_layernorm",
|
158 |
+
"model.layers.42.input_layernorm",
|
159 |
+
"model.layers.42.mlp.gate",
|
160 |
+
"model.layers.42.post_attention_layernorm",
|
161 |
+
"model.layers.43.input_layernorm",
|
162 |
+
"model.layers.43.mlp.gate",
|
163 |
+
"model.layers.43.post_attention_layernorm",
|
164 |
+
"model.layers.44.input_layernorm",
|
165 |
+
"model.layers.44.mlp.gate",
|
166 |
+
"model.layers.44.post_attention_layernorm",
|
167 |
+
"model.layers.45.input_layernorm",
|
168 |
+
"model.layers.45.mlp.gate",
|
169 |
+
"model.layers.45.post_attention_layernorm",
|
170 |
+
"model.layers.46.input_layernorm",
|
171 |
+
"model.layers.46.mlp.gate",
|
172 |
+
"model.layers.46.post_attention_layernorm",
|
173 |
+
"model.layers.47.input_layernorm",
|
174 |
+
"model.layers.47.mlp.gate",
|
175 |
+
"model.layers.47.post_attention_layernorm"
|
176 |
+
],
|
177 |
+
"quant_method": "fp8",
|
178 |
+
"weight_block_size": [
|
179 |
+
128,
|
180 |
+
128
|
181 |
+
]
|
182 |
+
},
|
183 |
+
"rms_norm_eps": 1e-06,
|
184 |
+
"rope_scaling": null,
|
185 |
+
"rope_theta": 10000000,
|
186 |
+
"router_aux_loss_coef": 0.001,
|
187 |
+
"sliding_window": null,
|
188 |
+
"tie_word_embeddings": false,
|
189 |
+
"torch_dtype": "bfloat16",
|
190 |
+
"transformers_version": "4.54.0",
|
191 |
+
"unsloth_fixed": true,
|
192 |
+
"use_cache": true,
|
193 |
+
"use_sliding_window": false,
|
194 |
+
"vocab_size": 151936
|
195 |
+
}
|
generation_config.json
ADDED
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_from_model_config": true,
|
3 |
+
"bos_token_id": 151643,
|
4 |
+
"eos_token_id": 151645,
|
5 |
+
"transformers_version": "4.51.3"
|
6 |
+
}
|
merges.txt
ADDED
The diff for this file is too large to render.
See raw diff
|
|
model-00001-of-00004.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:fed0a80c29eac54690eb6a39499c80aae9df06d04189479bb74b649411a9b419
|
3 |
+
size 10001462368
|
model-00002-of-00004.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:c72b1debd3bc4e55e1c6db6919e82d22de2c9d5cbd6d46f89cb1ba51b05bdc90
|
3 |
+
size 10000577408
|
model-00003-of-00004.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:84a55173edab143768a98307114b71dc51245124f116a893f310141d43bc4302
|
3 |
+
size 10000577448
|
model-00004-of-00004.safetensors
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:169d89f49b646a0a8329d9a2570650f5f5a0eb78740cb1952b76caab2f21c09e
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size 1173001360
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model.safetensors.index.json
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special_tokens_map.json
ADDED
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{
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"additional_special_tokens": [
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"<|im_start|>",
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"<|im_end|>",
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"<|object_ref_start|>",
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"<|object_ref_end|>",
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"<|box_start|>",
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"<|box_end|>",
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"<|quad_start|>",
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"<|quad_end|>",
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"<|vision_start|>",
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"<|vision_end|>",
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"<|vision_pad|>",
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"<|image_pad|>",
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"<|video_pad|>"
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],
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"eos_token": {
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}
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}
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tokenizer.json
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
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size 11422654
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tokenizer_config.json
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@@ -0,0 +1,241 @@
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{
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240 |
+
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n {{- messages[0].content + '\\n\\n' }}\n {%- endif %}\n {{- \"# 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>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\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\" }}\n{%- else %}\n {%- if messages[0].role == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n {%- set index = (messages|length - 1) - loop.index0 %}\n {%- 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>')) %}\n {%- set ns.multi_step_tool = false %}\n {%- set ns.last_query_index = index %}\n {%- endif %}\n{%- endfor %}\n{%- for message in messages %}\n {%- if message.content is string %}\n {%- set content = message.content %}\n {%- else %}\n {%- set content = '' %}\n {%- endif %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {%- set reasoning_content = '' %}\n {%- if message.reasoning_content is string %}\n {%- set reasoning_content = message.reasoning_content %}\n {%- else %}\n {%- if '</think>' in content %}\n {%- set reasoning_content = content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n {%- set content = content.split('</think>')[-1].lstrip('\\n') %}\n {%- endif %}\n {%- endif %}\n {%- if loop.index0 > ns.last_query_index %}\n {%- if loop.last or (not loop.last and reasoning_content) %}\n {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content.strip('\\n') + '\\n</think>\\n\\n' + content.lstrip('\\n') }}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- endif %}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- endif %}\n {%- if message.tool_calls %}\n {%- for tool_call in message.tool_calls %}\n {%- if (loop.first and content) or (not loop.first) %}\n {{- '\\n' }}\n {%- endif %}\n {%- if tool_call.function %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {%- if tool_call.arguments is string %}\n {{- tool_call.arguments }}\n {%- else %}\n {{- tool_call.arguments | tojson }}\n {%- endif %}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {%- endif %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n {%- if enable_thinking is defined and enable_thinking is false %}\n {{- '<think>\\n\\n</think>\\n\\n' }}\n {%- endif %}\n{%- endif %}"
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}
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vocab.json
ADDED
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