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Yi-1.5-34B-32K

Open Source 01-ai Released 2024-05-13
-- 34.0B params 32.8K context Open Source

About this model

πŸ™ GitHub β€’ πŸ‘Ύ Discord β€’ 🐀 Twitter β€’ πŸ’¬ WeChat
πŸ“ Paper β€’ πŸ’ͺ Tech Blog β€’ πŸ™Œ FAQ β€’ πŸ“— Learning Hub

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 β€’ πŸ€— Hugging Face β€’ πŸ€– ModelScope β€’ 🟣 wisemodel
Yi-1.5-34B-Chat-16K β€’ πŸ€— Hugging Face β€’ πŸ€– ModelScope β€’ 🟣 wisemodel
Yi-1.5-9B-Chat β€’ πŸ€— Hugging Face β€’ πŸ€– ModelScope β€’ 🟣 wisemodel
Yi-1.5-9B-Chat-16K β€’ πŸ€— Hugging Face β€’ πŸ€– ModelScope β€’ 🟣 wisemodel
Yi-1.5-6B-Chat β€’ πŸ€— Hugging Face β€’ πŸ€– ModelScope β€’ 🟣 wisemodel
  • Base models
Name Download
Yi-1.5-34B β€’ πŸ€— Hugging Face β€’ πŸ€– ModelScope β€’ 🟣 wisemodel
Yi-1.5-34B-32K β€’ πŸ€— Hugging Face β€’ πŸ€– ModelScope β€’ 🟣 wisemodel
Yi-1.5-9B β€’ πŸ€— Hugging Face β€’ πŸ€– ModelScope β€’ 🟣 wisemodel
Yi-1.5-9B-32K β€’ πŸ€— Hugging Face β€’ πŸ€– ModelScope β€’ 🟣 wisemodel
Yi-1.5-6B β€’ πŸ€— Hugging Face β€’ πŸ€– ModelScope β€’ 🟣 wisemodel

Benchmarks

  • Chat models

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

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

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  • Base models

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

image/png

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

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Quick Start

For getting up and running with Yi-1.5 models quickly, see README.

Benchmark Scores

ARC
65.6
BBH
76.4
GPQA
37.4
MATH
41.7
MBPP
65.5
MMLU
77.1
GSM8K
82.7
MMLU-Pro
48.3
HellaSwag
85.9
HumanEval
46.3
TruthfulQA
53.9

Technical Specs

  • Parameters: 34.0B
  • Architecture: Transformer
  • Context Window: 32,768 tokens
  • Input Modalities: text

Hardware Requirements

  • VRAM: 69.2 GB
  • Compute: Single NVIDIA A100 or A800 80GB GPU for BF16 inference with 32K context