File size: 8,337 Bytes
69c99d0
 
436e78d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
69c99d0
a291bf0
ccc62ae
a291bf0
af70757
a291bf0
 
 
 
 
af70757
a291bf0
 
af70757
a291bf0
 
 
 
 
 
 
 
 
 
616fc5a
a291bf0
616fc5a
 
a291bf0
616fc5a
6afa72f
616fc5a
 
 
 
 
fb8ac6f
 
0a16ba7
 
 
 
 
6afa72f
0a16ba7
6afa72f
0a16ba7
 
 
704c6e4
 
 
0a16ba7
 
 
 
 
6afa72f
 
 
0a16ba7
 
 
616fc5a
 
 
 
 
af70757
22b0ac8
241f9ee
22b0ac8
1dc6e2b
22b0ac8
241f9ee
22b0ac8
af70757
22b0ac8
0a16ba7
 
241f9ee
0a16ba7
 
 
241f9ee
 
616fc5a
 
0a16ba7
 
436e78d
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
---
license: apache-2.0
model-index:
- name: Yi-1.5-9B-Chat
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 63.65
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=01-ai/Yi-1.5-9B-Chat
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 80.94
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=01-ai/Yi-1.5-9B-Chat
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 71.01
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=01-ai/Yi-1.5-9B-Chat
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 52.67
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=01-ai/Yi-1.5-9B-Chat
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 77.19
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=01-ai/Yi-1.5-9B-Chat
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 71.87
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=01-ai/Yi-1.5-9B-Chat
      name: Open LLM Leaderboard
---
<div align="center">

<picture> 
  <img src="https://raw.githubusercontent.com/01-ai/Yi/main/assets/img/Yi_logo_icon_light.svg" width="150px">
</picture>

</div>

<p align="center">
  <a href="https://github.com/01-ai">πŸ™ GitHub</a> β€’
  <a href="https://discord.gg/hYUwWddeAu">πŸ‘Ύ Discord</a> β€’
  <a href="https://twitter.com/01ai_yi">🐀 Twitter</a> β€’
  <a href="https://github.com/01-ai/Yi-1.5/issues/2">πŸ’¬ WeChat</a> 
  <br/>
  <a href="https://arxiv.org/abs/2403.04652">πŸ“ Paper</a> β€’
  <a href="https://github.com/01-ai/Yi/tree/main?tab=readme-ov-file#faq">πŸ™Œ FAQ</a> β€’
  <a href="https://github.com/01-ai/Yi/tree/main?tab=readme-ov-file#learning-hub">πŸ“— Learning Hub</a>
</p>

# Intro

Yi-1.5 is an upgraded version of Yi. It is continuously pre-trained on Yi with a high-quality corpus of 500B tokens and fine-tuned on 3M diverse fine-tuning samples. 

Compared with Yi, Yi-1.5 delivers stronger performance in coding, math, reasoning, and instruction-following capability, while still maintaining excellent capabilities in language understanding, commonsense reasoning, and reading comprehension.

<div align="center">
  
Model | Context Length | Pre-trained Tokens
| :------------: | :------------: | :------------: |
| Yi-1.5 | 4K, 16K, 32K | 3.6T

</div>

# Models

- Chat models

  <div align="center">
  
  | Name            | Download                                                                                                                                                            |
  | --------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
  | Yi-1.5-34B-Chat | β€’ [πŸ€— Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) β€’ [πŸ€– ModelScope](https://www.modelscope.cn/organization/01ai) |
  | Yi-1.5-34B-Chat-16K  | β€’ [πŸ€— Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) β€’ [πŸ€– ModelScope](https://www.modelscope.cn/organization/01ai) |
  | Yi-1.5-9B-Chat  | β€’ [πŸ€— Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) β€’ [πŸ€– ModelScope](https://www.modelscope.cn/organization/01ai) |
  | Yi-1.5-9B-Chat-16K  | β€’ [πŸ€— Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) β€’ [πŸ€– ModelScope](https://www.modelscope.cn/organization/01ai) |
  | Yi-1.5-6B-Chat  | β€’ [πŸ€— Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) β€’ [πŸ€– ModelScope](https://www.modelscope.cn/organization/01ai) |
  
  </div>

- Base models

  <div align="center">
  
  | Name       | Download                                                                                                                                                            |
  | ---------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
  | Yi-1.5-34B | β€’ [πŸ€— Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) β€’ [πŸ€– ModelScope](https://www.modelscope.cn/organization/01ai) |
  | Yi-1.5-34B-32K | β€’ [πŸ€— Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) β€’ [πŸ€– ModelScope](https://www.modelscope.cn/organization/01ai) |
  | Yi-1.5-9B | β€’ [πŸ€— Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) β€’ [πŸ€– ModelScope](https://www.modelscope.cn/organization/01ai) |
  | Yi-1.5-9B-32K  | β€’ [πŸ€— Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) β€’ [πŸ€– ModelScope](https://www.modelscope.cn/organization/01ai) |
  | Yi-1.5-6B  | β€’ [πŸ€— Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) β€’ [πŸ€– ModelScope](https://www.modelscope.cn/organization/01ai) |
  
  </div>

# Benchmarks

- Chat models

  Yi-1.5-34B-Chat is on par with or excels beyond larger models in most benchmarks.

  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/656d9adce8bf55919aca7c3f/KcsJ9Oc1VnEmfCDEJc5cd.png)

  Yi-1.5-9B-Chat is the top performer among similarly sized open-source models.

  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/656d9adce8bf55919aca7c3f/xf6pLg5jqRCwjlh6m3t6_.png)

- Base models

  Yi-1.5-34B is on par with or excels beyond larger models in some benchmarks.

  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/656d9adce8bf55919aca7c3f/BwU7QM-03dZvZzwdIE1xY.png)

  Yi-1.5-9B is the top performer among similarly sized open-source models.

  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/656d9adce8bf55919aca7c3f/y-EYSYPT-3aWLJ0x8R94F.png)

# Quick Start

For getting up and running with Yi-1.5 models quickly, see [README](https://github.com/01-ai/Yi-1.5).


# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_01-ai__Yi-1.5-9B-Chat)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |69.56|
|AI2 Reasoning Challenge (25-Shot)|63.65|
|HellaSwag (10-Shot)              |80.94|
|MMLU (5-Shot)                    |71.01|
|TruthfulQA (0-shot)              |52.67|
|Winogrande (5-shot)              |77.19|
|GSM8k (5-shot)                   |71.87|