---
base_model: cloudyu/Yi-34Bx2-MoE-60B
license: cc-by-nc-4.0
model_creator: cloudyu
model_name: Yi 34Bx2 MoE 60B
model_type: mistral
quantized_by: Second State Inc.
tags:
- moe
---

<!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://github.com/LlamaEdge/LlamaEdge/raw/dev/assets/logo.svg" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
<!-- header end -->

# Yi-34Bx2-MoE-60B-GGUF

## Original Model

[cloudyu/Yi-34Bx2-MoE-60B](https://huggingface.co/cloudyu/Yi-34Bx2-MoE-60B)

## Run with LlamaEdge

- LlamaEdge version: [v0.2.8](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.2.8) and above

- Prompt template

  - Prompt type: `chatml`

  - Prompt string

    ```text
    <|im_start|>system
    {system_message}<|im_end|>
    <|im_start|>user
    {prompt}<|im_end|>
    <|im_start|>assistant
    ```

  - Reverse prompt: `<|im_end|>`

- Context size: `7168`

- Run as LlamaEdge service

  ```bash
  wasmedge --dir .:. --nn-preload default:GGML:AUTO:Yi-34Bx2-MoE-60B-Q5_K_M.gguf llama-api-server.wasm -p chatml -r '<|im_end|>'
  ```

- Run as LlamaEdge command app

  ```bash
  wasmedge --dir .:. --nn-preload default:GGML:AUTO:Yi-34Bx2-MoE-60B-Q5_K_M.gguf llama-chat.wasm -p chatml -r '<|im_end|>'
  ```

## Quantized GGUF Models

| Name | Quant method | Bits | Size | Use case |
| ---- | ---- | ---- | ---- | ----- |
| [Yi-34Bx2-MoE-60B-Q2_K.gguf](https://huggingface.co/second-state/Yi-34Bx2-MoE-60B-GGUF/blob/main/Yi-34Bx2-MoE-60B-Q2_K.gguf)     | Q2_K   | 2 | 22.4 GB| smallest, significant quality loss - not recommended for most purposes |
| [Yi-34Bx2-MoE-60B-Q3_K_L.gguf](https://huggingface.co/second-state/Yi-34Bx2-MoE-60B-GGUF/blob/main/Yi-34Bx2-MoE-60B-Q3_K_L.gguf) | Q3_K_L | 3 | 31.8 GB| small, substantial quality loss |
| [Yi-34Bx2-MoE-60B-Q3_K_M.gguf](https://huggingface.co/second-state/Yi-34Bx2-MoE-60B-GGUF/blob/main/Yi-34Bx2-MoE-60B-Q3_K_M.gguf) | Q3_K_M | 3 | 29.2 GB| very small, high quality loss |
| [Yi-34Bx2-MoE-60B-Q3_K_S.gguf](https://huggingface.co/second-state/Yi-34Bx2-MoE-60B-GGUF/blob/main/Yi-34Bx2-MoE-60B-Q3_K_S.gguf) | Q3_K_S | 3 | 26.3 GB| very small, high quality loss |
| [Yi-34Bx2-MoE-60B-Q4_0.gguf](https://huggingface.co/second-state/Yi-34Bx2-MoE-60B-GGUF/blob/main/Yi-34Bx2-MoE-60B-Q4_0.gguf)     | Q4_0   | 4 | 34.3 GB| legacy; small, very high quality loss - prefer using Q3_K_M |
| [Yi-34Bx2-MoE-60B-Q4_K_M.gguf](https://huggingface.co/second-state/Yi-34Bx2-MoE-60B-GGUF/blob/main/Yi-34Bx2-MoE-60B-Q4_K_M.gguf) | Q4_K_M | 4 | 36.7 GB| medium, balanced quality - recommended |
| [Yi-34Bx2-MoE-60B-Q4_K_S.gguf](https://huggingface.co/second-state/Yi-34Bx2-MoE-60B-GGUF/blob/main/Yi-34Bx2-MoE-60B-Q4_K_S.gguf) | Q4_K_S | 4 | 34.6 GB| small, greater quality loss |
| [Yi-34Bx2-MoE-60B-Q5_0.gguf](https://huggingface.co/second-state/Yi-34Bx2-MoE-60B-GGUF/blob/main/Yi-34Bx2-MoE-60B-Q5_0.gguf)     | Q5_0   | 5 | 41.9 GB| legacy; medium, balanced quality - prefer using Q4_K_M |
| [Yi-34Bx2-MoE-60B-Q5_K_M.gguf](https://huggingface.co/second-state/Yi-34Bx2-MoE-60B-GGUF/blob/main/Yi-34Bx2-MoE-60B-Q5_K_M.gguf) | Q5_K_M | 5 | 43.1 GB| large, very low quality loss - recommended |
| [Yi-34Bx2-MoE-60B-Q5_K_S.gguf](https://huggingface.co/second-state/Yi-34Bx2-MoE-60B-GGUF/blob/main/Yi-34Bx2-MoE-60B-Q5_K_S.gguf) | Q5_K_S | 5 | 41.9 GB| large, low quality loss - recommended |
| [Yi-34Bx2-MoE-60B-Q6_K.gguf](https://huggingface.co/second-state/Yi-34Bx2-MoE-60B-GGUF/blob/main/Yi-34Bx2-MoE-60B-Q6_K.gguf)     | Q6_K   | 6 | 49.9 GB| very large, extremely low quality loss |