--- base_model: Qwen/CodeQwen1.5-7B-Chat language: - en license: other license_name: tongyi-qianwen license_link: https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat/blob/main/LICENSE pipeline_tag: text-generation tags: - chat - llama-cpp - gguf-my-repo --- # hellork/CodeQwen1.5-7B-Chat-IQ4_NL-GGUF This model was converted to GGUF format from [`Qwen/CodeQwen1.5-7B-Chat`](https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat) 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/CodeQwen1.5-7B-Chat) 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 ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo hellork/CodeQwen1.5-7B-Chat-IQ4_NL-GGUF --hf-file codeqwen1.5-7b-chat-iq4_nl-imat.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo hellork/CodeQwen1.5-7B-Chat-IQ4_NL-GGUF --hf-file codeqwen1.5-7b-chat-iq4_nl-imat.gguf -c 2048 ``` ### The Ship's Computer: [whisper_dictation](https://github.com/themanyone/whisper_dictation) 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. ```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 cd whisper_dictation ./whisper_cpp_client.py ``` See [the docs](https://github.com/themanyone/whisper_dictation) for tips on integrating with llama.cpp server, enabling the computer to talk back, draw AI images, carry out voice commands, and other features. ### 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/CodeQwen1.5-7B-Chat-IQ4_NL-GGUF --hf-file codeqwen1.5-7b-chat-iq4_nl-imat.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo hellork/CodeQwen1.5-7B-Chat-IQ4_NL-GGUF --hf-file codeqwen1.5-7b-chat-iq4_nl-imat.gguf -c 2048 ```