README.md

---
base_model: maywell/Qwen2-7B-Multilingual-RP
language:
- en
- ko
- ja
- zh
- es
license: apache-2.0
tags:
- llama-cpp
- gguf-my-repo
---

# hellork/Qwen2-7B-Multilingual-RP-IQ4_NL-GGUF
This model was converted to GGUF format from [`maywell/Qwen2-7B-Multilingual-RP`](https://huggingface.co/maywell/Qwen2-7B-Multilingual-RP) 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/maywell/Qwen2-7B-Multilingual-RP) for more details on the model.

## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)

```bash
brew install llama.cpp

```

# Or compile it to take advantage of Nvidia CUDA hardware:

```bash
git clone https://github.com/ggerganov/llama.cpp.git
cd llama*
# look at docs for other hardware builds or to make sure none of this has changed.

cmake -B build -DGGML_CUDA=ON
CMAKE_ARGS="-DGGML_CUDA=on" cmake --build build --config Release # -j6 (optional: use a number less than the number of cores)

# If your version of gcc is > 12 and it gives errors, use conda to install gcc-12 and activate it.
# Run the above cmake commands again.
# Then run conda deactivate and re-run the last line once more to link the build outside of conda.
```

Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo hellork/Qwen2-7B-Multilingual-RP-IQ4_NL-GGUF --hf-file qwen2-7b-multilingual-rp-iq4_nl-imat.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo hellork/Qwen2-7B-Multilingual-RP-IQ4_NL-GGUF --hf-file qwen2-7b-multilingual-rp-iq4_nl-imat.gguf -c 2048
```

### The Ship's Computer:

Interact with this model by speaking to it. Lean, fast, & private, networked speech to text, AI images, multi-modal voice chat, control apps, webcam, and sound with less than 4GiB of VRAM.
[whisper_dictation](https://github.com/themanyone/whisper_dictation)

*Quick start*
```bash
git clone -b main --single-branch https://github.com/themanyone/whisper_dictation.git
pip install -r whisper_dictation/requirements.txt

git clone https://github.com/ggerganov/whisper.cpp
cd whisper.cpp
GGML_CUDA=1 make -j # assuming CUDA is available. see docs
ln -s server ~/.local/bin/whisper_cpp_server # (just put it somewhere in $PATH)
whisper_cpp_server -l en -m models/ggml-tiny.en.bin --port 7777

# -ngl option assumes CUDA or othr AI acceleration is available. see docs
llama-server --hf-repo hellork/calme-2.1-qwen2-7b-IQ4_NL-GGUF --hf-file qwen2-7b-multilingual-rp-iq4_nl-imat.gguf -c 2048 -ngl 17 --port 8888

cd whisper_dictation
./whisper_cpp_client.py
```

### Install llama.cpp via git:

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 hellork/Qwen2-7B-Multilingual-RP-IQ4_NL-GGUF --hf-file qwen2-7b-multilingual-rp-iq4_nl-imat.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo hellork/Qwen2-7B-Multilingual-RP-IQ4_NL-GGUF --hf-file qwen2-7b-multilingual-rp-iq4_nl-imat.gguf -c 2048
```