---
base_model: Qwen/Qwen2.5-7B-Instruct-1M-1M
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen2.5-7B-Instruct-1M/blob/main/LICENSE
model_creator: Qwen
model_name: Qwen2.5-7B-Instruct-1M
quantized_by: Second State Inc.
language:
- en
pipeline_tag: text-generation
tags:
- chat
library_name: transformers
---
# Qwen2.5-7B-Instruct-1M-GGUF
## Original Model
[Qwen/Qwen2.5-7B-Instruct-1M](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct-1M)
## Run with LlamaEdge
- LlamaEdge version: [v0.16.2](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.16.2)
- Prompt template
- Prompt type: `chatml`
- Prompt string
```text
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
```
- Context size: `1010000` (generation 8192 tokens)
- Run as LlamaEdge service
```bash
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Qwen2.5-7B-Instruct-1M-Q5_K_M.gguf \
llama-api-server.wasm \
--model-name Qwen2.5-7B-Instruct-1M \
--prompt-template chatml \
--ctx-size 1010000
```
- Run as LlamaEdge command app
```bash
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Qwen2.5-7B-Instruct-1M-Q5_K_M.gguf \
llama-chat.wasm \
--prompt-template chatml \
--ctx-size 1010000
```
## Quantized GGUF Models
| Name | Quant method | Bits | Size | Use case |
| ---- | ---- | ---- | ---- | ----- |
| [Qwen2.5-7B-Instruct-1M-Q2_K.gguf](https://huggingface.co/second-state/Qwen2.5-7B-Instruct-1M-GGUF/blob/main/Qwen2.5-7B-Instruct-1M-Q2_K.gguf) | Q2_K | 2 | 3.02 GB| smallest, significant quality loss - not recommended for most purposes |
| [Qwen2.5-7B-Instruct-1M-Q3_K_L.gguf](https://huggingface.co/second-state/Qwen2.5-7B-Instruct-1M-GGUF/blob/main/Qwen2.5-7B-Instruct-1M-Q3_K_L.gguf) | Q3_K_L | 3 | 4.09 GB| small, substantial quality loss |
| [Qwen2.5-7B-Instruct-1M-Q3_K_M.gguf](https://huggingface.co/second-state/Qwen2.5-7B-Instruct-1M-GGUF/blob/main/Qwen2.5-7B-Instruct-1M-Q3_K_M.gguf) | Q3_K_M | 3 | 3.81 GB| very small, high quality loss |
| [Qwen2.5-7B-Instruct-1M-Q3_K_S.gguf](https://huggingface.co/second-state/Qwen2.5-7B-Instruct-1M-GGUF/blob/main/Qwen2.5-7B-Instruct-1M-Q3_K_S.gguf) | Q3_K_S | 3 | 3.49 GB| very small, high quality loss |
| [Qwen2.5-7B-Instruct-1M-Q4_0.gguf](https://huggingface.co/second-state/Qwen2.5-7B-Instruct-1M-GGUF/blob/main/Qwen2.5-7B-Instruct-1M-Q4_0.gguf) | Q4_0 | 4 | 4.43 GB| legacy; small, very high quality loss - prefer using Q3_K_M |
| [Qwen2.5-7B-Instruct-1M-Q4_K_M.gguf](https://huggingface.co/second-state/Qwen2.5-7B-Instruct-1M-GGUF/blob/main/Qwen2.5-7B-Instruct-1M-Q4_K_M.gguf) | Q4_K_M | 4 | 4.68 GB| medium, balanced quality - recommended |
| [Qwen2.5-7B-Instruct-1M-Q4_K_S.gguf](https://huggingface.co/second-state/Qwen2.5-7B-Instruct-1M-GGUF/blob/main/Qwen2.5-7B-Instruct-1M-Q4_K_S.gguf) | Q4_K_S | 4 | 4.46 GB| small, greater quality loss |
| [Qwen2.5-7B-Instruct-1M-Q5_0.gguf](https://huggingface.co/second-state/Qwen2.5-7B-Instruct-1M-GGUF/blob/main/Qwen2.5-7B-Instruct-1M-Q5_0.gguf) | Q5_0 | 5 | 5.32 GB| legacy; medium, balanced quality - prefer using Q4_K_M |
| [Qwen2.5-7B-Instruct-1M-Q5_K_M.gguf](https://huggingface.co/second-state/Qwen2.5-7B-Instruct-1M-GGUF/blob/main/Qwen2.5-7B-Instruct-1M-Q5_K_M.gguf) | Q5_K_M | 5 | 5.44 GB| large, very low quality loss - recommended |
| [Qwen2.5-7B-Instruct-1M-Q5_K_S.gguf](https://huggingface.co/second-state/Qwen2.5-7B-Instruct-1M-GGUF/blob/main/Qwen2.5-7B-Instruct-1M-Q5_K_S.gguf) | Q5_K_S | 5 | 5.32 GB| large, low quality loss - recommended |
| [Qwen2.5-7B-Instruct-1M-Q6_K.gguf](https://huggingface.co/second-state/Qwen2.5-7B-Instruct-1M-GGUF/blob/main/Qwen2.5-7B-Instruct-1M-Q6_K.gguf) | Q6_K | 6 | 6.25 GB| very large, extremely low quality loss |
| [Qwen2.5-7B-Instruct-1M-Q8_0.gguf](https://huggingface.co/second-state/Qwen2.5-7B-Instruct-1M-GGUF/blob/main/Qwen2.5-7B-Instruct-1M-Q8_0.gguf) | Q8_0 | 8 | 8.21 GB| very large, extremely low quality loss - not recommended |
| [Qwen2.5-7B-Instruct-1M-f16.gguf](https://huggingface.co/second-state/Qwen2.5-7B-Instruct-1M-GGUF/blob/main/Qwen2.5-7B-Instruct-1M-f16.gguf) | f16 | 16 | 15.2 GB| |
*Quantized with llama.cpp b4466*