|
--- |
|
license: apache-2.0 |
|
license_link: https://huggingface.co./Qwen/Qwen2.5-3B-Instruct-GGUF/blob/main/LICENSE |
|
language: |
|
- en |
|
base_model: |
|
- Qwen/Qwen2.5-3B-Instruct |
|
pipeline_tag: text-generation |
|
quantized_by: mukel |
|
tags: |
|
- chat |
|
- qwen |
|
--- |
|
|
|
# GGUF models for qwen2.java |
|
Pure .gguf Q4_0 and Q8_0 quantizations of Qwen 2.5 models, ready to consume by `qwen2.java`. |
|
|
|
In the wild, Q8_0 quantizations are fine, but Q4_0 quantizations are rarely pure e.g. the token embeddings are quantized with Q6_K, instead of Q4_0. |
|
A pure Q4_0 quantization can be generated from a high precision (F32, F16, BFLOAT16) .gguf source with the llama-quantize utility from llama.cpp as follows: |
|
|
|
``` |
|
./llama-quantize --pure ./Qwen-2.5-7B-Instruct-BF16.gguf ./Qwen-2.5-7B-Instruct-Q4_0.gguf Q4_0 |
|
``` |
|
|
|
## Introduction |
|
|
|
Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2: |
|
|
|
- Significantly **more knowledge** and has greatly improved capabilities in **coding** and **mathematics**, thanks to our specialized expert models in these domains. |
|
- Significant improvements in **instruction following**, **generating long texts** (over 8K tokens), **understanding structured data** (e.g, tables), and **generating structured outputs** especially JSON. **More resilient to the diversity of system prompts**, enhancing role-play implementation and condition-setting for chatbots. |
|
- **Long-context Support** up to 128K tokens and can generate up to 8K tokens. |
|
- **Multilingual support** for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more. |
|
|
|
For more details, please refer to our [blog](https://qwenlm.github.io/blog/qwen2.5/), [GitHub](https://github.com/QwenLM/Qwen2.5), and [Documentation](https://qwen.readthedocs.io/en/latest/). |
|
|
