This model was converted to GGUF format from
AdaptLLM/medicine-chat using llama.cpp via the ggml.ai's
GGUF-my-repo space.
Refer to the
original model card for more details on the model.
1brew install llama.cpp
2
Invoke the llama.cpp server or the CLI.
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
1git clone -b main --single-branch https://github.com/themanyone/whisper_dictation.git
2pip install -r whisper_dictation/requirements.txt
3
4git clone https://github.com/ggerganov/whisper.cpp
5cd whisper.cpp
6GGML_CUDA=1 make -j # assuming CUDA is available. see docs
7ln -s server ~/.local/bin/whisper_cpp_server # (just put it somewhere in $PATH)
8
9# -ngl option assums AI accelerator like CUDA is available
10llama-server --hf-repo hellork/medicine-chat-IQ4_NL-GGUF --hf-file medicine-chat-iq4_nl-imat.gguf -c 2048 -ngl 17 --port 8888
11whisper_cpp_server -l en -m models/ggml-tiny.en.bin --port 7777
12cd whisper_dictation
13./whisper_cpp_client.py
See
the docs for tips on integrating with llama.cpp server, enabling the computer to talk back, draw AI images, carry out voice commands, and other features.
Note: You can also try this checkpoint with the
usage steps listed in the Llama.cpp repo.
Step 1: Clone llama.cpp from GitHub.
Step 3: Run inference through the main binary.