Qwen2-7B-Multilingual-RP-IQ4_NL-GGUF

hellork/Qwen2-7B-Multilingual-RP-IQ4_NL-GGUF

This model was converted to GGUF format from maywell/Qwen2-7B-Multilingual-RP using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Use with llama.cpp

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

brew install llama.cpp

Or compile it to take advantage of Nvidia CUDA hardware:

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:

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:

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

Quick start

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