Edit model card

Triangle104/Llama-3.1-SuperNova-Lite-Q6_K-GGUF

This model was converted to GGUF format from arcee-ai/Llama-3.1-SuperNova-Lite using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.


Model details:

Overview

Llama-3.1-SuperNova-Lite is an 8B parameter model developed by Arcee.ai, based on the Llama-3.1-8B-Instruct architecture. It is a distilled version of the larger Llama-3.1-405B-Instruct model, leveraging offline logits extracted from the 405B parameter variant. This 8B variation of Llama-3.1-SuperNova maintains high performance while offering exceptional instruction-following capabilities and domain-specific adaptability.

The model was trained using a state-of-the-art distillation pipeline and an instruction dataset generated with EvolKit, ensuring accuracy and efficiency across a wide range of tasks. For more information on its training, visit blog.arcee.ai.

Llama-3.1-SuperNova-Lite excels in both benchmark performance and real-world applications, providing the power of large-scale models in a more compact, efficient form ideal for organizations seeking high performance with reduced resource requirements.


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 Triangle104/Llama-3.1-SuperNova-Lite-Q6_K-GGUF --hf-file llama-3.1-supernova-lite-q6_k.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/Llama-3.1-SuperNova-Lite-Q6_K-GGUF --hf-file llama-3.1-supernova-lite-q6_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 Triangle104/Llama-3.1-SuperNova-Lite-Q6_K-GGUF --hf-file llama-3.1-supernova-lite-q6_k.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/Llama-3.1-SuperNova-Lite-Q6_K-GGUF --hf-file llama-3.1-supernova-lite-q6_k.gguf -c 2048
Downloads last month
23
GGUF
Model size
8.03B params
Architecture
llama

6-bit

Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for Triangle104/Llama-3.1-SuperNova-Lite-Q6_K-GGUF

Dataset used to train Triangle104/Llama-3.1-SuperNova-Lite-Q6_K-GGUF

Collection including Triangle104/Llama-3.1-SuperNova-Lite-Q6_K-GGUF

Evaluation results