Quantization made by Richard Erkhov.

[Github](https://github.com/RichardErkhov)

[Discord](https://discord.gg/pvy7H8DZMG)

[Request more models](https://github.com/RichardErkhov/quant_request)


Yi-1.5-34B-Chat-16K - GGUF
- Model creator: https://huggingface.co/01-ai/
- Original model: https://huggingface.co/01-ai/Yi-1.5-34B-Chat-16K/


| Name | Quant method | Size |
| ---- | ---- | ---- |
| [Yi-1.5-34B-Chat-16K.Q2_K.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.Q2_K.gguf) | Q2_K | 11.94GB |
| [Yi-1.5-34B-Chat-16K.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.IQ3_XS.gguf) | IQ3_XS | 13.26GB |
| [Yi-1.5-34B-Chat-16K.IQ3_S.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.IQ3_S.gguf) | IQ3_S | 13.99GB |
| [Yi-1.5-34B-Chat-16K.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.Q3_K_S.gguf) | Q3_K_S | 13.93GB |
| [Yi-1.5-34B-Chat-16K.IQ3_M.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.IQ3_M.gguf) | IQ3_M | 14.5GB |
| [Yi-1.5-34B-Chat-16K.Q3_K.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.Q3_K.gguf) | Q3_K | 15.51GB |
| [Yi-1.5-34B-Chat-16K.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.Q3_K_M.gguf) | Q3_K_M | 15.51GB |
| [Yi-1.5-34B-Chat-16K.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.Q3_K_L.gguf) | Q3_K_L | 16.89GB |
| [Yi-1.5-34B-Chat-16K.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.IQ4_XS.gguf) | IQ4_XS | 17.36GB |
| [Yi-1.5-34B-Chat-16K.Q4_0.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.Q4_0.gguf) | Q4_0 | 18.13GB |
| [Yi-1.5-34B-Chat-16K.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.IQ4_NL.gguf) | IQ4_NL | 18.3GB |
| [Yi-1.5-34B-Chat-16K.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.Q4_K_S.gguf) | Q4_K_S | 18.25GB |
| [Yi-1.5-34B-Chat-16K.Q4_K.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.Q4_K.gguf) | Q4_K | 19.24GB |
| [Yi-1.5-34B-Chat-16K.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.Q4_K_M.gguf) | Q4_K_M | 19.24GB |
| [Yi-1.5-34B-Chat-16K.Q4_1.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.Q4_1.gguf) | Q4_1 | 20.1GB |
| [Yi-1.5-34B-Chat-16K.Q5_0.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.Q5_0.gguf) | Q5_0 | 22.08GB |
| [Yi-1.5-34B-Chat-16K.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.Q5_K_S.gguf) | Q5_K_S | 22.08GB |
| [Yi-1.5-34B-Chat-16K.Q5_K.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.Q5_K.gguf) | Q5_K | 22.65GB |
| [Yi-1.5-34B-Chat-16K.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.Q5_K_M.gguf) | Q5_K_M | 22.65GB |
| [Yi-1.5-34B-Chat-16K.Q5_1.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.Q5_1.gguf) | Q5_1 | 24.05GB |
| [Yi-1.5-34B-Chat-16K.Q6_K.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.Q6_K.gguf) | Q6_K | 26.28GB |
| [Yi-1.5-34B-Chat-16K.Q8_0.gguf](https://huggingface.co/RichardErkhov/01-ai_-_Yi-1.5-34B-Chat-16K-gguf/blob/main/Yi-1.5-34B-Chat-16K.Q8_0.gguf) | Q8_0 | 34.03GB |




Original model description:
---
license: apache-2.0
---
<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">🐙 GitHub</a> •
  <a href="https://discord.gg/hYUwWddeAu">👾 Discord</a> •
  <a href="https://twitter.com/01ai_yi">🐤 Twitter</a> •
  <a href="https://github.com/01-ai/Yi-1.5/issues/2">💬 WeChat</a> 
  <br/>
  <a href="https://arxiv.org/abs/2403.04652">📝 Paper</a> •
  <a href="https://01-ai.github.io/">💪 Tech Blog</a> •
  <a href="https://github.com/01-ai/Yi/tree/main?tab=readme-ov-file#faq">🙌 FAQ</a> •
  <a href="https://github.com/01-ai/Yi/tree/main?tab=readme-ov-file#learning-hub">📗 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 | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI)|
  | Yi-1.5-34B-Chat-16K  | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI) |
  | Yi-1.5-9B-Chat  | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI) |
  | Yi-1.5-9B-Chat-16K  | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI) |
  | Yi-1.5-6B-Chat  | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI) |
  
  </div>

- Base models

  <div align="center">
  
  | Name       | Download                                                                                                                                                            |
  | ---------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
  | Yi-1.5-34B | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI) |
  | Yi-1.5-34B-32K | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI) |
  | Yi-1.5-9B | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI) |
  | Yi-1.5-9B-32K  | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI) |
  | Yi-1.5-6B  | • [🤗 Hugging Face](https://huggingface.co/collections/01-ai/yi-15-2024-05-663f3ecab5f815a3eaca7ca8) • [🤖 ModelScope](https://www.modelscope.cn/organization/01ai) • [🟣 wisemodel](https://wisemodel.cn/organization/01.AI) |
  
  </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).