Quark-270m-Instruct-GGUF/README.md

language, license, tags, library_name, pipeline_tag, base_model

language	license	tags	library_name	pipeline_tag	base_model
it en	apache-2.0	text-generation causal-lm bilingual italian english small-language-model trained-from-scratch quark instruct sft chat llama-cpp gguf-my-repo	transformers	text-generation	ThingAI/Quark-270m-Instruct

usermma/Quark-270m-Instruct-GGUF

This model was converted to GGUF format from ThingAI/Quark-270m-Instruct using llama.cpp. 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

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo usermma/Quark-270m-Instruct-GGUF --hf-file quark-270m-instruct-q2_k.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo usermma/Quark-270m-Instruct-GGUF --hf-file quark-270m-instruct-q2_k.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

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 usermma/Quark-270m-Instruct-GGUF --hf-file quark-270m-instruct-q2_k.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo usermma/Quark-270m-Instruct-GGUF --hf-file quark-270m-instruct-q2_k.gguf -c 2048