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hellork/medicine-chat-IQ4_NL-GGUF
medicine-chat-IQ4_NL-GGUF is a text generation model from hellork. Use it when you need the model to write or continue text. The card lists the license as llama2.
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.
Downloads · 30 days
107
19% of all-time downloads
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.gguf3.8 GB · 100%
From the Hugging Face model README
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.
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
llama-cli --hf-repo hellork/medicine-chat-IQ4_NL-GGUF --hf-file medicine-chat-iq4_nl-imat.gguf -p "The meaning to life and the universe is"
llama-server --hf-repo hellork/medicine-chat-IQ4_NL-GGUF --hf-file medicine-chat-iq4_nl-imat.gguf -c 2048
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
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)
# -ngl option assums AI accelerator like CUDA is available
llama-server --hf-repo hellork/medicine-chat-IQ4_NL-GGUF --hf-file medicine-chat-iq4_nl-imat.gguf -c 2048 -ngl 17 --port 8888
whisper_cpp_server -l en -m models/ggml-tiny.en.bin --port 7777
cd whisper_dictation
./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.
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/medicine-chat-IQ4_NL-GGUF --hf-file medicine-chat-iq4_nl-imat.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo hellork/medicine-chat-IQ4_NL-GGUF --hf-file medicine-chat-iq4_nl-imat.gguf -c 2048