metadata

base_model: nvidia/Llama-3.1-Minitron-4B-Width-Base
license: other
license_name: nvidia-open-model-license
license_link: >-
  https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf
tags:
  - llama-cpp
  - gguf-my-repo
datasets:
  - Gryphe/Opus-WritingPrompts

ijohn07/Llama-3.1-Minitron-4B-Width-Base-Q5_K_M-GGUF

This model was converted to GGUF format from nvidia/Llama-3.1-Minitron-4B-Width-Base using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Added the Datasets 1&2 from Gryphe/Opus-WritingPrompts

datasets/Gryphe/Opus-WritingPrompts

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 ijohn07/Llama-3.1-Minitron-4B-Width-Base-Q5_K_M-GGUF --hf-file llama-3.1-minitron-4b-width-base-q5_k_m-imat.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo ijohn07/Llama-3.1-Minitron-4B-Width-Base-Q5_K_M-GGUF --hf-file llama-3.1-minitron-4b-width-base-q5_k_m-imat.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 ijohn07/Llama-3.1-Minitron-4B-Width-Base-Q5_K_M-GGUF --hf-file llama-3.1-minitron-4b-width-base-q5_k_m-imat.gguf -p "The meaning to life and the universe is"

./llama-server --hf-repo ijohn07/Llama-3.1-Minitron-4B-Width-Base-Q5_K_M-GGUF --hf-file llama-3.1-minitron-4b-width-base-q5_k_m-imat.gguf -c 2048