Update README.md
Browse files
README.md
CHANGED
@@ -11,11 +11,11 @@ library_name: transformers
|
|
11 |
|
12 |
<h3 align="center">
|
13 |
<b>
|
14 |
-
<span
|
15 |
<br/>
|
16 |
Unlocking the Reasoning Potential of Language Model<br/>From Pretraining to Posttraining
|
17 |
<br/>
|
18 |
-
<span
|
19 |
<br/>
|
20 |
</b>
|
21 |
</h3>
|
@@ -35,7 +35,41 @@ library_name: transformers
|
|
35 |
|
36 |
<br/>
|
37 |
|
38 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
39 |
|
40 |
## I. Introduction
|
41 |
|
@@ -122,7 +156,7 @@ MiMo-7B series
|
|
122 |
|
123 |
### SGLang Inference
|
124 |
|
125 |
-
Thanks to the [
|
126 |
|
127 |
Example Script
|
128 |
|
@@ -132,9 +166,14 @@ python3 -m uv pip install "sglang[all] @ git+https://github.com/sgl-project/sgla
|
|
132 |
|
133 |
# Launch SGLang Server
|
134 |
python3 -m sglang.launch_server --model-path XiaomiMiMo/MiMo-7B-Base --host 0.0.0.0 --trust-remote-code
|
|
|
|
|
|
|
|
|
|
|
135 |
```
|
136 |
|
137 |
-
Detailed usage can be found in [SGLang documents](https://docs.sglang.ai/backend/send_request.html).
|
138 |
|
139 |
### vLLM inference
|
140 |
|
@@ -223,7 +262,7 @@ print(tokenizer.decode(output.tolist()[0]))
|
|
223 |
```bibtex
|
224 |
@misc{coreteam2025mimounlockingreasoningpotential,
|
225 |
title={MiMo: Unlocking the Reasoning Potential of Language Model -- From Pretraining to Posttraining},
|
226 |
-
author={
|
227 |
year={2025},
|
228 |
eprint={2505.07608},
|
229 |
archivePrefix={arXiv},
|
|
|
11 |
|
12 |
<h3 align="center">
|
13 |
<b>
|
14 |
+
<span>βββββββββββββββββββββββββββββββββββββββββ</span>
|
15 |
<br/>
|
16 |
Unlocking the Reasoning Potential of Language Model<br/>From Pretraining to Posttraining
|
17 |
<br/>
|
18 |
+
<span>βββββββββββββββββββββββββββββββββββββββββ</span>
|
19 |
<br/>
|
20 |
</b>
|
21 |
</h3>
|
|
|
35 |
|
36 |
<br/>
|
37 |
|
38 |
+
---
|
39 |
+
|
40 |
+
## Updates
|
41 |
+
|
42 |
+
[2025.05.30] We scaled the SFT dataset from approximately 500K to 6M instances and continuously expanding the RL training window size from 32K to 48K, the performance of [MiMo-7B-RL-0530](https://huggingface.co/XiaomiMiMo/MiMo-7B-RL-0530) on AIME24 can be continuously improved and eventually surpass that of DeepSeek R1 (79.8).
|
43 |
+
|
44 |
+
<table>
|
45 |
+
<thead>
|
46 |
+
<tr>
|
47 |
+
<th>Benchmark</th>
|
48 |
+
<th>MiMo-7B-RL</th>
|
49 |
+
<th>MiMo-7B-RL-0530</th>
|
50 |
+
</tr>
|
51 |
+
</thead>
|
52 |
+
<tbody>
|
53 |
+
<tr>
|
54 |
+
<td colspan="3"><strong>Mathematics</strong></td>
|
55 |
+
<p align="center">
|
56 |
+
<td rowspan="11"><img width="80%" src="https://github.com/XiaomiMiMo/MiMo/raw/main/figures/length.jpg?raw=true"></td>
|
57 |
+
</p>
|
58 |
+
</tr>
|
59 |
+
<tr><td>MATH500<br/>(Pass@1)</td><td>95.8</td><td>97.2</td></tr>
|
60 |
+
<tr><td>AIME 2024<br/>(Pass@1)</td><td>68.2</td><td>80.1</td></tr>
|
61 |
+
<tr><td>AIME 2025<br/>(Pass@1)</td><td>55.4</td><td>70.2</td></tr>
|
62 |
+
<tr><td colspan="3"><strong>Code</strong></td></tr>
|
63 |
+
<tr><td>LiveCodeBench v5<br/>(Pass@1)</td><td>57.8</td><td>60.9</td></tr>
|
64 |
+
<tr><td>LiveCodeBench v6<br/>(Pass@1)</td><td>49.3</td><td>52.2</td></tr>
|
65 |
+
<tr><td colspan="3"><strong>STEM</strong></td></tr>
|
66 |
+
<tr><td>GPQA-Diamond<br/>(Pass@1)</td><td>54.4</td><td>60.6</td></tr>
|
67 |
+
<tr><td colspan="3"><strong>General</strong></td></tr>
|
68 |
+
<tr><td>Alignbench1.1<br/>(Evaluated by GPT4.1)</td><td>6.9</td><td>7.4</td></tr>
|
69 |
+
</tbody>
|
70 |
+
</table>
|
71 |
+
|
72 |
+
---
|
73 |
|
74 |
## I. Introduction
|
75 |
|
|
|
156 |
|
157 |
### SGLang Inference
|
158 |
|
159 |
+
Thanks to the [MiMo model support](https://github.com/sgl-project/sglang/pull/5921) and [MTP](https://github.com/sgl-project/sglang/pull/6059) from the SGLang team, we supported MiMo in SGLang mainstream.
|
160 |
|
161 |
Example Script
|
162 |
|
|
|
166 |
|
167 |
# Launch SGLang Server
|
168 |
python3 -m sglang.launch_server --model-path XiaomiMiMo/MiMo-7B-Base --host 0.0.0.0 --trust-remote-code
|
169 |
+
|
170 |
+
# Launch MTP Server
|
171 |
+
python3 -m sglang.launch_server --model-path XiaomiMiMo/MiMo-7B-Base --trust-remote-code \
|
172 |
+
--speculative-algorithm EAGLE --speculative-num-steps 1 --speculative-eagle-topk 1 \
|
173 |
+
--speculative-num-draft-tokens 2 --mem-fraction 0.5
|
174 |
```
|
175 |
|
176 |
+
Detailed usage can be found in [SGLang documents](https://docs.sglang.ai/backend/send_request.html).
|
177 |
|
178 |
### vLLM inference
|
179 |
|
|
|
262 |
```bibtex
|
263 |
@misc{coreteam2025mimounlockingreasoningpotential,
|
264 |
title={MiMo: Unlocking the Reasoning Potential of Language Model -- From Pretraining to Posttraining},
|
265 |
+
author={LLM-Core-Team Xiaomi},
|
266 |
year={2025},
|
267 |
eprint={2505.07608},
|
268 |
archivePrefix={arXiv},
|