File size: 2,658 Bytes
6455801 8d1d5e2 6455801 b0c6a62 6455801 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 |
---
library_name: transformers
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507/blob/main/LICENSE
pipeline_tag: text-generation
base_model: Qwen/Qwen3-30B-A3B-Instruct-2507
tags:
- llama-cpp
- gguf-my-repo
---
# Triangle104/Qwen3-30B-A3B-Instruct-2507-Q4_K_S-GGUF
This model was converted to GGUF format from [`Qwen/Qwen3-30B-A3B-Instruct-2507`](https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507) for more details on the model.
---
We introduce the updated version of the Qwen3-30B-A3B non-thinking mode, named Qwen3-30B-A3B-Instruct-2507, featuring the following key enhancements:
- Significant improvements in general capabilities, including instruction following, logical reasoning, text comprehension, mathematics, science, coding and tool usage.
- Substantial gains in long-tail knowledge coverage across multiple languages.
- Markedly better alignment with user preferences in subjective and open-ended tasks, enabling more helpful responses and higher-quality text generation.
- Enhanced capabilities in 256K long-context understanding.
---
## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
```bash
brew install llama.cpp
```
Invoke the llama.cpp server or the CLI.
### CLI:
```bash
llama-cli --hf-repo Triangle104/Qwen3-30B-A3B-Instruct-2507-Q4_K_S-GGUF --hf-file qwen3-30b-a3b-instruct-2507-q4_k_s.gguf -p "The meaning to life and the universe is"
```
### Server:
```bash
llama-server --hf-repo Triangle104/Qwen3-30B-A3B-Instruct-2507-Q4_K_S-GGUF --hf-file qwen3-30b-a3b-instruct-2507-q4_k_s.gguf -c 2048
```
Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```
Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```
Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo Triangle104/Qwen3-30B-A3B-Instruct-2507-Q4_K_S-GGUF --hf-file qwen3-30b-a3b-instruct-2507-q4_k_s.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo Triangle104/Qwen3-30B-A3B-Instruct-2507-Q4_K_S-GGUF --hf-file qwen3-30b-a3b-instruct-2507-q4_k_s.gguf -c 2048
```
|