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chai_sus_yi

Text Generation
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text-generation-inference
Inference Endpoints
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  1. README.md +417 -0
  2. config.json +28 -0
  3. pytorch_model-00001-of-00007.bin +3 -0
  4. pytorch_model-00002-of-00007.bin +3 -0
  5. pytorch_model-00003-of-00007.bin +3 -0
  6. pytorch_model-00004-of-00007.bin +3 -0
  7. pytorch_model-00005-of-00007.bin +3 -0
  8. pytorch_model-00006-of-00007.bin +3 -0
  9. pytorch_model-00007-of-00007.bin +3 -0
  10. pytorch_model.bin.index.json +550 -0
  11. special_tokens_map.json +6 -0
  12. tokenizer.json +0 -0
  13. tokenizer.model +3 -0
  14. tokenizer_config.json +38 -0
README.md ADDED
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+ ---
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+ license: other
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+ license_name: yi-license
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+ license_link: LICENSE
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+ widget:
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+ - example_title: SUS-Chat
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+ text: hi
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+ output:
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+ text: ' Hello! How can I assist you today?'
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+ pipeline_tag: text-generation
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+ ---
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+ # 🐷SUS-Chat: Instruction tuning done right
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+
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+ <p align="left">
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+ <a href="README_CN.md">中文</a>&nbsp ｜ &nbspEnglish&nbsp
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+ </p>
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+
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+ <br><br>
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+
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+ <div align="center">
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+
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+ <p align="center">
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+ <img src="https://github.com/SUSTech-IDEA/SUS-Chat/raw/main/assets/sustech.svg?sanitize=true" width="200px">
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+ <img src="https://github.com/SUSTech-IDEA/SUS-Chat/raw/main/assets/ccnl.png?sanitize=true" width="200px">
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+ </p>
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+
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+ <div style="display: inline-block;">
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+
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+ <a rel="noopener nofollow" href="https://github.com/SUSTech-IDEA/SUS-Chat/issues">
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+ <img src="https://img.shields.io/github/issues/SUSTech-IDEA/SUS-Chat?logo=github" style="margin: 0 0;">
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+ </a>
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+
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+ </div>
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+
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+ <div style="display: inline-block;">
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+
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+ <a href="https://huggingface.co/SUSTech">
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+ <img src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-SUSTech-blue" style="margin: 0 0;">
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+ </a>
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+
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+ </div>
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+
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+ <div style="display: inline-block;">
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+
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+ <a rel="noopener nofollow" href="https://www.modelscope.cn/organization/sustc/">
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+ <img src="https://img.shields.io/badge/🤖ModelScope-sustc-blue" style="margin: 0 0;">
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+ </a>
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+
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+ </div>
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+
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+ <a href="https://wisemodel.cn/organization/SUSTech">
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+ <img src="https://img.shields.io/badge/WiseModel-SUSTech-blue"> </a>
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+
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+ <div style="display: inline-block;">
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+
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+ <a rel="noopener nofollow" href="https://github.com/SUSTech-IDEA/SUS-Chat/blob/main/LICENSE">
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+ <img src="https://img.shields.io/badge/Code_License-Apache_2.0-lightblue" style="margin: 0 0;">
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+ </a>
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+
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+ </div>
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+
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+ <div style="display: inline-block;">
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+
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+ <a rel="noopener nofollow" href="https://github.com/01-ai/Yi/blob/main/MODEL_LICENSE_AGREEMENT.txt">
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+ <img src="https://img.shields.io/badge/Model_License-Model_Agreement-lightblue" style="margin: 0 0;">
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+ </a>
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+
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+ </div>
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+
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+ <div style="display: inline-block;">
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+
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+ <a rel="noopener nofollow" href="mailto:oss@data.sustech.edu.cn">
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+ <img src="https://img.shields.io/badge/✉️-data@sustech.edu.cn-FFE01B" style="margin: 0 0;">
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+ </a>
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+
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+ </div>
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+
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+ </div>
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+
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+ # News
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+
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+ - 2024-1-04: 🔥 `cloudyu` created a series of top ranked
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+ [MOE](https://huggingface.co/cloudyu/Yi-34Bx2-MoE-60B) based on our
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+ model
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+
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+ - 2023-12-09: 🔥 `Tigerbot` variant has been
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+ [deleted](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/438),
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+ `SUS-Chat-34B` is now the the top-ranked LLaMA model and the
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+ top-ranked chat model.
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+
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+ - 2023-12-07: SUS-Chat-34B is now available on
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+ [WiseModel🧠](https://wisemodel.cn/model/SUSTech/SUS-Chat-34B).
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+
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+ - 2023-12-06: Try [SUS-Chat-34B
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+ chat-ui](https://huggingface.co/spaces/SUSTech/SUS-Chat-34B).
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+
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+ - 2023-12-05: SUS-Chat-34B is now available on
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+ [ModelScope🤖](https://www.modelscope.cn/models/SUSTC/SUS-Chat-34B/summary)
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+
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+ - 2023-12-05: SUS-Chat-34B is ranked 2nd in [Open LLM
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+ leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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+ and surpassed all models under 70B.
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+
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+ - 2023-12-01: SUS-Chat-34B is now available on
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+ [HuggingFace🤗](https://huggingface.co/SUSTech/SUS-Chat-34B).
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+
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+ # Introduction
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+
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+ <img src="https://hackmd.io/_uploads/HJlDtzhBa.png" id="fig-sus"
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+ alt="Figure 1: DALL·E 2023-12-01 11.03.28 - An imposing, majestic wild boar combined with elements of a futuristic transformer robot. The boar itself should be intricately blended with these tra" />
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+
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+ **SUS-Chat-34B** is a 34B bilingual Chinese-English dialogue model,
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+ jointly released by the **[Southern University of Science and
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+ Technology](https://huggingface.co/SUSTech)** and
115
+ **[IDEA-CCNL](https://huggingface.co/IDEA-CCNL)**. This model is based
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+ on [`01-ai/Yi-34B`](https://huggingface.co/01-ai/Yi-34B) and has been
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+ fine-tuned on millions of high-quality, multilingual instruction data.
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+ While maintaining the strong language capabilities of the base model,
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+ the SUS-Chat-34B model has improved the model’s response to human
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+ instructions through high-quality instruction fine-tuning and excels at
121
+ imitating human thought processes through chains of thought. It
122
+ introduces inter-instruction attention sharing in long texts, expanding
123
+ the window size from 4K to 8K, significantly enhancing the usability of
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+ multi-turn dialogues.
125
+
126
+ It has surpassed all models of the same size in almost all benchmark
127
+ tests and is better suited to meet the practical needs of complex
128
+ multilingual tasks. Compared to larger models, SUS-Chat-34B remains
129
+ highly competitive and has achieved state-of-the-art performance in our
130
+ comprehensive evaluations.
131
+
132
+ SUS-Chat-34B model has the following highlights:
133
+
134
+ 1. Large-scale complex instruction following data: Trained with 1.4
135
+ billion tokens of high-quality complex instruction data, covering
136
+ Chinese and English, multi-turn dialogues, mathematics, reasoning,
137
+ and various other types of instruction data;
138
+ 2. Strong performance in general tasks: The SUS-Chat-34B model excels
139
+ in numerous mainstream Chinese and English tasks, surpassing other
140
+ open-source instruction fine-tuned models of the same parameter
141
+ scale. It also competes well against models with larger parameter
142
+ scales;
143
+ 3. Longer context window and excellent multi-turn dialogue
144
+ capabilities: Currently, SUS-Chat-34B supports an 8K context window,
145
+ and is trained with a large amount of multi-turn instruction and
146
+ single-multi-turn mixed data, demonstrating remarkable capabilities
147
+ in long-text dialogue information focus and instruction follow-up.
148
+
149
+ SUS-Chat powerfully demonstrates that through the right instruction
150
+ fine-tuning, academic institutions can achieve better performance
151
+ without increasing model parameters, using open-source datasets and
152
+ models. This bridges the gap between academia and industry in large
153
+ language models and opens new possibilities for collaboration between
154
+ academic and industrial sectors.
155
+
156
+ # Performance
157
+
158
+ To better evaluate the performance of the SUS-Chat-34B model, we
159
+ conducted assessments across multiple benchmark tests and have
160
+ open-sourced the evaluation framework
161
+ [TLEM](https://huggingface.co/spaces/SUSTech/tlem) to facilitate
162
+ replication and comparison by other researchers.
163
+
164
+ In TLEM, we utilized various benchmark tests including MMLU, CMMLU,
165
+ C-Eval, BBH, GSM-8K, and MATH, to measure the model’s knowledge and
166
+ thinking capabilities. In these metrics, the SUS-Chat-34B model achieved
167
+ state-of-the-art performance. Additionally, we incorporated
168
+ [lm-eval](https://github.com/EleutherAI/lm-evaluation-harness) to test
169
+ SUS-Chat and similar models on winogrande, hellaswag, arc, and
170
+ truthful-qa, assessing the model’s common-sense reasoning ability and
171
+ susceptibility to illusions.
172
+
173
+ Overall, the SUS-Chat-34B model significantly outperformed models of
174
+ similar scale and achieved the most advanced comprehensive performance.
175
+
176
+ <img
177
+ src="https://github.com/SUSTech-IDEA/SUS-Chat/raw/main/assets/radar.png"
178
+ id="fig-bench" alt="Figure 2: Benchmark" />
179
+
180
+ <div>
181
+
182
+ <table>
183
+ <colgroup>
184
+ <col style="width: 50%" />
185
+ <col style="width: 50%" />
186
+ </colgroup>
187
+ <tbody>
188
+ <tr class="odd">
189
+ <td style="text-align: center;"><div width="50.0%"
190
+ data-layout-align="center">
191
+ <h2 id="english-understanding">English Understanding</h2>
192
+ <table>
193
+ <thead>
194
+ <tr class="header">
195
+ <th style="text-align: right;">Model</th>
196
+ <th style="text-align: center;">mmlu (0-shot)</th>
197
+ </tr>
198
+ </thead>
199
+ <tbody>
200
+ <tr class="odd">
201
+ <td style="text-align: right;">GPT-4</td>
202
+ <td style="text-align: center;">83</td>
203
+ </tr>
204
+ <tr class="even">
205
+ <td style="text-align: right;">SUS-Chat-34B</td>
206
+ <td style="text-align: center;"><u>74.35</u></td>
207
+ </tr>
208
+ <tr class="odd">
209
+ <td style="text-align: right;">Qwen-72b-Chat</td>
210
+ <td style="text-align: center;"><strong>74.52</strong></td>
211
+ </tr>
212
+ <tr class="even">
213
+ <td style="text-align: right;">Deepseek-68b-Chat</td>
214
+ <td style="text-align: center;">69.43</td>
215
+ </tr>
216
+ <tr class="odd">
217
+ <td style="text-align: right;">OrionStar-Yi-34B-Chat</td>
218
+ <td style="text-align: center;">68.51</td>
219
+ </tr>
220
+ <tr class="even">
221
+ <td style="text-align: right;">Yi-34B-Chat</td>
222
+ <td style="text-align: center;">66.96</td>
223
+ </tr>
224
+ </tbody>
225
+ </table>
226
+ </div></td>
227
+ <td style="text-align: center;"><div width="50.0%"
228
+ data-layout-align="center">
229
+ <h2 id="chinese-capabilities">Chinese Capabilities</h2>
230
+ <table>
231
+ <colgroup>
232
+ <col style="width: 34%" />
233
+ <col style="width: 32%" />
234
+ <col style="width: 32%" />
235
+ </colgroup>
236
+ <thead>
237
+ <tr class="header">
238
+ <th style="text-align: right;">Model</th>
239
+ <th style="text-align: center;">cmmlu (0-shot)</th>
240
+ <th style="text-align: center;">C-Eval (0-shot)<a href="#fn1"
241
+ class="footnote-ref" id="fnref1"
242
+ role="doc-noteref"><sup>1</sup></a></th>
243
+ </tr>
244
+ </thead>
245
+ <tbody>
246
+ <tr class="odd">
247
+ <td style="text-align: right;">GPT-4</td>
248
+ <td style="text-align: center;">71</td>
249
+ <td style="text-align: center;">69.9</td>
250
+ </tr>
251
+ <tr class="even">
252
+ <td style="text-align: right;">SUS-Chat-34B</td>
253
+ <td style="text-align: center;"><strong>78.68</strong></td>
254
+ <td style="text-align: center;"><strong>82.42</strong></td>
255
+ </tr>
256
+ <tr class="odd">
257
+ <td style="text-align: right;">Qwen-72b-Chat</td>
258
+ <td style="text-align: center;"><u>77.02</u></td>
259
+ <td style="text-align: center;"><u>77.22</u></td>
260
+ </tr>
261
+ <tr class="even">
262
+ <td style="text-align: right;">Deepseek-68b-Chat</td>
263
+ <td style="text-align: center;">48.51</td>
264
+ <td style="text-align: center;">59.7</td>
265
+ </tr>
266
+ <tr class="odd">
267
+ <td style="text-align: right;">OrionStar-Yi-34B-Chat</td>
268
+ <td style="text-align: center;">66.88</td>
269
+ <td style="text-align: center;">65.13</td>
270
+ </tr>
271
+ <tr class="even">
272
+ <td style="text-align: right;">Yi-34B-Chat</td>
273
+ <td style="text-align: center;">55.16</td>
274
+ <td style="text-align: center;">77.16</td>
275
+ </tr>
276
+ </tbody>
277
+ </table>
278
+ </div></td>
279
+ </tr>
280
+ </tbody>
281
+ </table>
282
+ <section id="footnotes" class="footnotes footnotes-end-of-document"
283
+ role="doc-endnotes">
284
+ <hr />
285
+ <ol>
286
+ <li id="fn1"><p>C-Eval results are evaluated on the validation
287
+ datasets<a href="#fnref1" class="footnote-back"
288
+ role="doc-backlink">↩︎</a></p></li>
289
+ </ol>
290
+ </section>
291
+
292
+ </div>
293
+
294
+ ## Math & Reasoning
295
+
296
+ | Model | gsm8k (0-shot) | MATH (0-shot) | BBH (0-shot) |
297
+ |----------------------:|:--------------:|:-------------:|:------------:|
298
+ | GPT-4 | 91.4 | 45.8 | 86.7 |
299
+ | SUS-Chat-34B | **80.06** | 28.7 | 67.62 |
300
+ | Qwen-72b-Chat | <u>76.57</u> | **35.9** | **72.63** |
301
+ | Deepseek-68b-Chat | 74.45 | <u>29.56</u> | <u>69.73</u> |
302
+ | OrionStar-Yi-34B-Chat | 54.36 | 12.8 | 62.88 |
303
+ | Yi-34B-Chat | 63.76 | 10.02 | 61.54 |
304
+
305
+ ## More Tasks
306
+
307
+ | Model | winogrande (5-shot) | arc (25-shot) | hellaswag (10-shot) | TruthfulQA mc1 (0-shot) | TruthfulQA mc2 (0-shot) |
308
+ |----------------------:|:-------------------:|:-------------:|:-------------------:|:-----------------------:|:-----------------------:|
309
+ | GPT-4 | — | 94.5 | 91.4 | 59.00 | — |
310
+ | SUS-Chat-34B | **81.22** | <u>81.54</u> | 83.79 | **40.64** | **57.47** |
311
+ | Qwen-72b-Chat | 76.09 | **82.10** | <u>86.06</u> | 39.17 | <u>56.37</u> |
312
+ | Deepseek-68b-Chat | <u>80.58</u> | 81.29 | **87.02** | <u>40.02</u> | 50.64 |
313
+ | OrionStar-Yi-34B-Chat | 77.27 | 80.19 | 84.54 | 36.47 | 53.24 |
314
+ | Yi-34B-Chat | 76.64 | 70.66 | 82.29 | 38.19 | 54.57 |
315
+
316
+ ## Overall
317
+
318
+ | Model | Average |
319
+ |----------------------:|:---------:|
320
+ | SUS-Chat-34B | **69.05** |
321
+ | Qwen-72b-Chat | 68.41 |
322
+ | Deepseek-68b-Chat | 62.91 |
323
+ | OrionStar-Yi-34B-Chat | 60.21 |
324
+ | Yi-34B-Chat | 59.72 |
325
+
326
+ To reproduce the results, please start a corresponding vllm server and
327
+ refer to
328
+ [here](https://sustech-tlem.static.hf.space/index.html#start-evaluating-your-model-in-3-line).
329
+
330
+ # Usage
331
+
332
+ SUS-Chat-34B is a standard LLaMA model and should be seamlessly
333
+ compatible with the LLaMA ecosystem. We provide the following example to
334
+ demonstrate how it can be used for multi-turn dialogues.
335
+
336
+ Feel free to [open an
337
+ issue](https://github.com/SUSTech-IDEA/SUS-Chat/issues) if you have any
338
+ questions.
339
+
340
+ ``` python
341
+ from transformers import AutoModelForCausalLM, AutoTokenizer # 🤗 Transformers, or
342
+ # from modelscope import AutoModelForCausalLM, AutoTokenizer # 🤖 ModelScope
343
+
344
+ def chat_template(messages):
345
+ history = ""
346
+ for message in messages:
347
+ match message:
348
+ case {"role": "user", "content": message}:
349
+ history += f"### Human: {message}\n\n### Assistant: "
350
+ case {"role": "assistant", "content": message}:
351
+ history += message
352
+ return history
353
+
354
+
355
+ model_path = "SUSTech/SUS-Chat-34B"
356
+ # model_path = "SUSTC/SUS-Chat-34B" # ModelScope
357
+
358
+ tokenizer = AutoTokenizer.from_pretrained(model_path, use_fast=False)
359
+ model = AutoModelForCausalLM.from_pretrained(
360
+ model_path, device_map="auto", torch_dtype="auto"
361
+ ).eval()
362
+
363
+ messages = [{"role": "user", "content": "hi"}]
364
+
365
+ input_ids = tokenizer.encode(
366
+ chat_template(messages), return_tensors="pt", add_special_tokens=False
367
+ ).to("cuda")
368
+ output_ids = model.generate(input_ids.to("cuda"), max_length=256)
369
+ response = tokenizer.decode(
370
+ output_ids[0][input_ids.shape[1] :], skip_special_tokens=False
371
+ )
372
+
373
+ messages.append({"role": "assistant", "content": response})
374
+
375
+ # Second round
376
+
377
+ messages.append({"role": "user", "content": "What is the capital of China?"})
378
+
379
+ input_ids = tokenizer.encode(
380
+ chat_template(messages), return_tensors="pt", add_special_tokens=False
381
+ ).to("cuda")
382
+ output_ids = model.generate(input_ids.to("cuda"), max_length=256)
383
+ response = tokenizer.decode(
384
+ output_ids[0][input_ids.shape[1] :], skip_special_tokens=False
385
+ )
386
+
387
+ messages.append({"role": "assistant", "content": response})
388
+ ```
389
+
390
+ # Limitations
391
+
392
+ SUS-Chat has only undergone supervised fine-tuning and has not yet been
393
+ trained on human preference learning. As a result, it may produce
394
+ unreasonable responses in some situations and exacerbate existing issues
395
+ in language models, including hallucinations, non-determinism, and
396
+ cumulative errors. To achieve better performance for downstream tasks,
397
+ we recommend adjusting the generation configuration parameters
398
+ accordingly.
399
+
400
+ # Disclaimer
401
+
402
+ During the training process, we used data compliance check algorithms to
403
+ ensure the compliance of the training model as much as possible. Due to
404
+ the complexity of the data and the diverse use cases of language models,
405
+ we cannot guarantee that the model will produce correct and reasonable
406
+ outputs in all scenarios. Please be aware that there is still a risk of
407
+ the model generating problematic outputs. We will not be responsible for
408
+ any risks or issues arising from misuse, misguidance, illegal use, and
409
+ related misinformation, as well as data security issues related to the
410
+ model.
411
+
412
+ # License
413
+
414
+ This model is developed entirely for academic research and free
415
+ commercial use, but it must adhere to the
416
+ [license](https://github.com/01-ai/Yi/blob/main/MODEL_LICENSE_AGREEMENT.txt)
417
+ from [01-ai](https://huggingface.co/01-ai).
config.json ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "01-ai/Yi-34B",
3
+ "architectures": [
4
+ "LlamaForCausalLM"
5
+ ],
6
+ "attention_bias": false,
7
+ "bos_token_id": 1,
8
+ "eos_token_id": 2,
9
+ "hidden_act": "silu",
10
+ "hidden_size": 7168,
11
+ "initializer_range": 0.02,
12
+ "intermediate_size": 20480,
13
+ "max_position_embeddings": 8192,
14
+ "model_type": "llama",
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+ "legacy": true,
32
+ "model_max_length": 4096,
33
+ "pad_token": "<unk>",
34
+ "sp_model_kwargs": {},
35
+ "tokenizer_class": "LlamaTokenizer",
36
+ "unk_token": "<unk>",
37
+ "use_default_system_prompt": false
38
+ }