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---
base_model: Qwen/Qwen2.5-Math-1.5B-Instruct
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen2.5-Math-1.5B-Instruct/blob/main/LICENSE
model_creator: Qwen
model_name: Qwen2.5-Math-1.5B-Instruct
quantized_by: Second State Inc.
language:
- en
pipeline_tag: text-generation
library_name: transformers
tags:
- code
- codeqwen
- chat
- qwen
- qwen-coder
---
<!-- 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 -->
# Qwen2.5-Math-1.5B-Instruct-GGUF
## Original Model
[Qwen/Qwen2.5-Math-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Math-1.5B-Instruct)
## Run with LlamaEdge
- LlamaEdge version: coming soon
<!-- - LlamaEdge version: [v0.14.3](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.14.3) -->
<!-- - Prompt template
- Prompt type: coming soon
- Prompt string
- File-Level Code Completion (Fill in the middle)
```text
<|fim_prefix|>{prefix_code}<|fim_suffix|>{suffix_code}<|fim_middle|>
```
*Reference: https://github.com/QwenLM/Qwen2.5-Coder?tab=readme-ov-file#3-file-level-code-completion-fill-in-the-middle*
- Repository-Level Code Completion
```text
<|repo_name|>{repo_name}
<|file_sep|>{file_path1}
{file_content1}
<|file_sep|>{file_path2}
{file_content2}
```
*Reference: https://github.com/QwenLM/Qwen2.5-Coder?tab=readme-ov-file#4-repository-level-code-completion*
- Context size: `128000`
- Run as LlamaEdge service
```bash
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Qwen2.5-Math-1.5B-Instruct-Q5_K_M.gguf \
llama-api-server.wasm \
--model-name Qwen2.5-Math-1.5B-Instruct \
--prompt-template chatml \
--ctx-size 128000
```
- Run as LlamaEdge command app
```bash
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Qwen2.5-Math-1.5B-Instruct-Q5_K_M.gguf \
llama-chat.wasm \
--prompt-template chatml \
--ctx-size 128000
``` -->
## Quantized GGUF Models
| Name | Quant method | Bits | Size | Use case |
| ---- | ---- | ---- | ---- | ----- |
| [Qwen2.5-Math-1.5B-Instruct-Q2_K.gguf](https://huggingface.co/second-state/Qwen2.5-Math-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Math-1.5B-Instruct-Q2_K.gguf) | Q2_K | 2 | 676 MB| smallest, significant quality loss - not recommended for most purposes |
| [Qwen2.5-Math-1.5B-Instruct-Q3_K_L.gguf](https://huggingface.co/second-state/Qwen2.5-Math-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Math-1.5B-Instruct-Q3_K_L.gguf) | Q3_K_L | 3 | 880 MB| small, substantial quality loss |
| [Qwen2.5-Math-1.5B-Instruct-Q3_K_M.gguf](https://huggingface.co/second-state/Qwen2.5-Math-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Math-1.5B-Instruct-Q3_K_M.gguf) | Q3_K_M | 3 | 824 MB| very small, high quality loss |
| [Qwen2.5-Math-1.5B-Instruct-Q3_K_S.gguf](https://huggingface.co/second-state/Qwen2.5-Math-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Math-1.5B-Instruct-Q3_K_S.gguf) | Q3_K_S | 3 | 761 MB| very small, high quality loss |
| [Qwen2.5-Math-1.5B-Instruct-Q4_0.gguf](https://huggingface.co/second-state/Qwen2.5-Math-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Math-1.5B-Instruct-Q4_0.gguf) | Q4_0 | 4 | 935 MB| legacy; small, very high quality loss - prefer using Q3_K_M |
| [Qwen2.5-Math-1.5B-Instruct-Q4_K_M.gguf](https://huggingface.co/second-state/Qwen2.5-Math-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Math-1.5B-Instruct-Q4_K_M.gguf) | Q4_K_M | 4 | 986 MB| medium, balanced quality - recommended |
| [Qwen2.5-Math-1.5B-Instruct-Q4_K_S.gguf](https://huggingface.co/second-state/Qwen2.5-Math-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Math-1.5B-Instruct-Q4_K_S.gguf) | Q4_K_S | 4 | 940 MB| small, greater quality loss |
| [Qwen2.5-Math-1.5B-Instruct-Q5_0.gguf](https://huggingface.co/second-state/Qwen2.5-Math-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Math-1.5B-Instruct-Q5_0.gguf) | Q5_0 | 5 | 1.10 GB| legacy; medium, balanced quality - prefer using Q4_K_M |
| [Qwen2.5-Math-1.5B-Instruct-Q5_K_M.gguf](https://huggingface.co/second-state/Qwen2.5-Math-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Math-1.5B-Instruct-Q5_K_M.gguf) | Q5_K_M | 5 | 1.13 GB| large, very low quality loss - recommended |
| [Qwen2.5-Math-1.5B-Instruct-Q5_K_S.gguf](https://huggingface.co/second-state/Qwen2.5-Math-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Math-1.5B-Instruct-Q5_K_S.gguf) | Q5_K_S | 5 | 1.10 GB| large, low quality loss - recommended |
| [Qwen2.5-Math-1.5B-Instruct-Q6_K.gguf](https://huggingface.co/second-state/Qwen2.5-Math-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Math-1.5B-Instruct-Q6_K.gguf) | Q6_K | 6 | 1.27 GB| very large, extremely low quality loss |
| [Qwen2.5-Math-1.5B-Instruct-Q8_0.gguf](https://huggingface.co/second-state/Qwen2.5-Math-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Math-1.5B-Instruct-Q8_0.gguf) | Q8_0 | 8 | 1.36 GB| very large, extremely low quality loss - not recommended |
| [Qwen2.5-Math-1.5B-Instruct-f16.gguf](https://huggingface.co/second-state/Qwen2.5-Math-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Math-1.5B-Instruct-f16.gguf) | f16 | 16 | 3.09 GB| |
*Quantized with llama.cpp b3751* |