Instructions to use hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF:IQ4_NL # Run inference directly in the terminal: llama cli -hf hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF:IQ4_NL
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF:IQ4_NL # Run inference directly in the terminal: llama cli -hf hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF:IQ4_NL
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF:IQ4_NL # Run inference directly in the terminal: ./llama-cli -hf hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF:IQ4_NL
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF:IQ4_NL # Run inference directly in the terminal: ./build/bin/llama-cli -hf hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF:IQ4_NL
Use Docker
docker model run hf.co/hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF:IQ4_NL
- LM Studio
- Jan
- Ollama
How to use hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF with Ollama:
ollama run hf.co/hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF:IQ4_NL
- Unsloth Desktop
- Docker Model Runner
How to use hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF with Docker Model Runner:
docker model run hf.co/hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF:IQ4_NL
- Lemonade
How to use hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF:IQ4_NL
Run and chat with the model
lemonade run user.deepseek-coder-6.7b-instruct-IQ4_NL-GGUF-IQ4_NL
List all available models
lemonade list
- Atomic Chat
| base_model: deepseek-ai/deepseek-coder-6.7b-instruct | |
| license: other | |
| license_name: deepseek | |
| license_link: LICENSE | |
| tags: | |
| - llama-cpp | |
| - gguf-my-repo | |
| # hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF | |
| This model was converted to GGUF format from [`deepseek-ai/deepseek-coder-6.7b-instruct`](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instruct) 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/deepseek-ai/deepseek-coder-6.7b-instruct) 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/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF --hf-file deepseek-coder-6.7b-instruct-iq4_nl-imat.gguf -p "The meaning to life and the universe is" | |
| ``` | |
| ### Server: | |
| ```bash | |
| llama-server --hf-repo hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF --hf-file deepseek-coder-6.7b-instruct-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 calme-2.1-qwen2-7b-iq4_nl-imat.gguf -c 2048 -ngl 17 --port 8888 | |
| cd whisper_dictation | |
| ./whisper_cpp_client.py | |
| ``` | |
| ### Install llama.cpp via git: | |
| Step 1: `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/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF --hf-file deepseek-coder-6.7b-instruct-iq4_nl-imat.gguf -p "The meaning to life and the universe is" | |
| ``` | |
| or | |
| ``` | |
| ./llama-server --hf-repo hellork/deepseek-coder-6.7b-instruct-IQ4_NL-GGUF --hf-file deepseek-coder-6.7b-instruct-iq4_nl-imat.gguf -c 2048 | |
| ``` | |