anester/Llama3.1-SuperDeepFuse-IQ4_NL-GGUF
This model was converted to GGUF format from agentlans/Llama3.1-SuperDeepFuse
using llama.cpp via the ggml.ai's GGUF-my-repo space.
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 anester/Llama3.1-SuperDeepFuse-IQ4_NL-GGUF --hf-file llama3.1-superdeepfuse-iq4_nl-imat.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo anester/Llama3.1-SuperDeepFuse-IQ4_NL-GGUF --hf-file llama3.1-superdeepfuse-iq4_nl-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 anester/Llama3.1-SuperDeepFuse-IQ4_NL-GGUF --hf-file llama3.1-superdeepfuse-iq4_nl-imat.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo anester/Llama3.1-SuperDeepFuse-IQ4_NL-GGUF --hf-file llama3.1-superdeepfuse-iq4_nl-imat.gguf -c 2048
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Base model
agentlans/Llama3.1-SuperDeepFuseEvaluation results
- averaged accuracy on IFEval (0-Shot)Open LLM Leaderboard77.620
- normalized accuracy on BBH (3-Shot)test set Open LLM Leaderboard29.220
- exact match on MATH Lvl 5 (4-Shot)test set Open LLM Leaderboard17.750
- acc_norm on GPQA (0-shot)Open LLM Leaderboard3.240
- acc_norm on MuSR (0-shot)Open LLM Leaderboard5.130
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard30.830