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
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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.
| Model | Context Length | Pre-trained Tokens |
|---|---|---|
| Yi-1.5 | 4K, 16K, 32K | 3.6T |
Models
Chat models
Name Download Yi-1.5-34B-Chat • 🤗 Hugging Face • 🤖 ModelScope Yi-1.5-34B-Chat-16K • 🤗 Hugging Face • 🤖 ModelScope Yi-1.5-9B-Chat • 🤗 Hugging Face • 🤖 ModelScope Yi-1.5-9B-Chat-16K • 🤗 Hugging Face • 🤖 ModelScope Yi-1.5-6B-Chat • 🤗 Hugging Face • 🤖 ModelScope Base models
Name Download Yi-1.5-34B • 🤗 Hugging Face • 🤖 ModelScope Yi-1.5-34B-32K • 🤗 Hugging Face • 🤖 ModelScope Yi-1.5-9B • 🤗 Hugging Face • 🤖 ModelScope Yi-1.5-9B-32K • 🤗 Hugging Face • 🤖 ModelScope Yi-1.5-6B • 🤗 Hugging Face • 🤖 ModelScope
Benchmarks
Chat models
Yi-1.5-34B-Chat is on par with or excels beyond larger models in most benchmarks.
Yi-1.5-9B-Chat is the top performer among similarly sized open-source models.
Base models
Yi-1.5-34B is on par with or excels beyond larger models in some benchmarks.
Yi-1.5-9B is the top performer among similarly sized open-source models.
Quick Start
For getting up and running with Yi-1.5 models quickly, see README.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| 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 |