Quantization made by Richard Erkhov.

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

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Qwen1.5-MoE-A2.7B - GGUF
- Model creator: https://huggingface.co/Qwen/
- Original model: https://huggingface.co/Qwen/Qwen1.5-MoE-A2.7B/


| Name | Quant method | Size |
| ---- | ---- | ---- |
| [Qwen1.5-MoE-A2.7B.Q2_K.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.Q2_K.gguf) | Q2_K | 5.49GB |
| [Qwen1.5-MoE-A2.7B.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.IQ3_XS.gguf) | IQ3_XS | 6.07GB |
| [Qwen1.5-MoE-A2.7B.IQ3_S.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.IQ3_S.gguf) | IQ3_S | 6.37GB |
| [Qwen1.5-MoE-A2.7B.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.Q3_K_S.gguf) | Q3_K_S | 6.37GB |
| [Qwen1.5-MoE-A2.7B.IQ3_M.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.IQ3_M.gguf) | IQ3_M | 6.46GB |
| [Qwen1.5-MoE-A2.7B.Q3_K.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.Q3_K.gguf) | Q3_K | 6.93GB |
| [Qwen1.5-MoE-A2.7B.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.Q3_K_M.gguf) | Q3_K_M | 6.93GB |
| [Qwen1.5-MoE-A2.7B.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.Q3_K_L.gguf) | Q3_K_L | 7.21GB |
| [Qwen1.5-MoE-A2.7B.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.IQ4_XS.gguf) | IQ4_XS | 7.4GB |
| [Qwen1.5-MoE-A2.7B.Q4_0.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.Q4_0.gguf) | Q4_0 | 7.59GB |
| [Qwen1.5-MoE-A2.7B.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.IQ4_NL.gguf) | IQ4_NL | 7.68GB |
| [Qwen1.5-MoE-A2.7B.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.Q4_K_S.gguf) | Q4_K_S | 8.11GB |
| [Qwen1.5-MoE-A2.7B.Q4_K.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.Q4_K.gguf) | Q4_K | 8.84GB |
| [Qwen1.5-MoE-A2.7B.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.Q4_K_M.gguf) | Q4_K_M | 8.84GB |
| [Qwen1.5-MoE-A2.7B.Q4_1.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.Q4_1.gguf) | Q4_1 | 8.41GB |
| [Qwen1.5-MoE-A2.7B.Q5_0.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.Q5_0.gguf) | Q5_0 | 9.22GB |
| [Qwen1.5-MoE-A2.7B.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.Q5_K_S.gguf) | Q5_K_S | 9.46GB |
| [Qwen1.5-MoE-A2.7B.Q5_K.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.Q5_K.gguf) | Q5_K | 10.09GB |
| [Qwen1.5-MoE-A2.7B.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.Q5_K_M.gguf) | Q5_K_M | 10.09GB |
| [Qwen1.5-MoE-A2.7B.Q5_1.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.Q5_1.gguf) | Q5_1 | 10.04GB |
| [Qwen1.5-MoE-A2.7B.Q6_K.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.Q6_K.gguf) | Q6_K | 11.89GB |
| [Qwen1.5-MoE-A2.7B.Q8_0.gguf](https://huggingface.co/RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-gguf/blob/main/Qwen1.5-MoE-A2.7B.Q8_0.gguf) | Q8_0 | 14.18GB |




Original model description:
---
license: other
license_name: tongyi-qianwen
license_link: >-
  https://huggingface.co/Qwen/Qwen1.5-MoE-A2.7B/blob/main/LICENSE
language:
- en
pipeline_tag: text-generation
tags:
- pretrained
- moe
---

# Qwen1.5-MoE-A2.7B


## Introduction

Qwen1.5-MoE is a transformer-based MoE decoder-only language model pretrained on a large amount of data. 

For more details, please refer to our [blog post](https://qwenlm.github.io/blog/qwen-moe/) and [GitHub repo](https://github.com/QwenLM/Qwen1.5).

## Model Details
Qwen1.5-MoE employs Mixture of Experts (MoE) architecture, where the models are upcycled from dense language models. For instance, `Qwen1.5-MoE-A2.7B` is upcycled from `Qwen-1.8B`. It has 14.3B parameters in total and 2.7B activated parameters during runtime, while achieving comparable performance to `Qwen1.5-7B`, it only requires 25% of the training resources. We also observed that the inference speed is 1.74 times that of `Qwen1.5-7B`.

## Requirements
The code of Qwen1.5-MoE has been in the latest Hugging face transformers and we advise you to build from source with command `pip install git+https://github.com/huggingface/transformers`, or you might encounter the following error:
```
KeyError: 'qwen2_moe'.
```

## Usage

We do not advise you to use base language models for text generation. Instead, you can apply post-training, e.g., SFT, RLHF, continued pretraining, etc., on this model.