---
base_model: 01-ai/Yi-1.5-9B-Chat-16K
pipeline_tag: text-generation
inference: false
model_creator: 01-AI
model_name: Yi-1.5-9B-Chat-16K
model_type: llama
language:
  - en
  - zh
library_name: transformers
license: apache-2.0
quantized_by: ThiloteE
tags:
  - text-generation-inference
  - transformers
  - GGUF
  - GPT4All

---
# About

<!-- ### quantize_version: 2 -->
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- Static quants of https://huggingface.co/01-ai/Yi-1.5-9B-Chat-16K
- Quantized with llama.cpp commit [c3776ca](https://github.com/ggerganov/llama.cpp/commit/c3776cacabce2ee35f172fb72be7a519752125fa) by [ThiloteE](https://huggingface.co/ThiloteE)

# Notes

These quants were created with a customized configuration that have been proven to not cause visible end of string (eos) tokens during inference with [GPT4All](https://www.nomic.ai/gpt4all).
The config.json, generation_config.json and  tokenizer_config.json differ from the original configuration as can be found in the original model's repository at the time of creation of these quants.

# Prompt Template (for GPT4All)

System Prompt:
```
<|im_start|>system
Below is an instruction that describes a task. Write a response that appropriately completes the request.<|im_end|>

```


Chat Template:
```
<|im_start|>user
%1<|im_end|>
<|im_start|>assistant
%2<|im_end|>

```

Do not miss the newlines at the end!

# Context Length

`16384`


# Provided Quants


| Link | Type | Size/GB | Notes |
|:-----|:-----|--------:|:------|
| [GGUF](https://huggingface.co/mradermacher/pstella-16b-GGUF/resolve/main/pstella-16b.Q4_K_M.gguf) | Q4_0 | 4.9 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/pstella-16b-GGUF/resolve/main/pstella-16b.f16.gguf) | f16 | 17.2 | 16 bpw, overkill |




# About GGUF

If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
more details, including on how to concatenate multi-part files.

Here is a handy graph by ikawrakow comparing some quant types (lower is better):

![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)

And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

# Thanks

I thank Mradermacher and TheBloke for Inspiration to this model card and their contributions to open source. I thank 3Simplex for everything.
Shoutout to the GPT4All and llama.cpp communities :-)


------

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# Original Model card:

---
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).


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