Triangle104/Llama-3.1-SuperNova-Lite-Q4_K_S-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-Q4_K_S-GGUF --hf-file llama-3.1-supernova-lite-q4_k_s.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo Triangle104/Llama-3.1-SuperNova-Lite-Q4_K_S-GGUF --hf-file llama-3.1-supernova-lite-q4_k_s.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-Q4_K_S-GGUF --hf-file llama-3.1-supernova-lite-q4_k_s.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo Triangle104/Llama-3.1-SuperNova-Lite-Q4_K_S-GGUF --hf-file llama-3.1-supernova-lite-q4_k_s.gguf -c 2048
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Base model
meta-llama/Llama-3.1-8BDataset used to train Triangle104/Llama-3.1-SuperNova-Lite-Q4_K_S-GGUF
Collection including Triangle104/Llama-3.1-SuperNova-Lite-Q4_K_S-GGUF
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard80.170
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard31.570
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard15.480
- acc_norm on GPQA (0-shot)Open LLM Leaderboard7.490
- acc_norm on MuSR (0-shot)Open LLM Leaderboard11.670
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard31.970