A newer version of this model is available:
Daemontatox/RA_Reasoner2.0
darkc0de/RA_Reasoner2.0-Q5_K_S-GGUF
This model was converted to GGUF format from Daemontatox/RA_Reasoner2.0
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 darkc0de/RA_Reasoner2.0-Q5_K_S-GGUF --hf-file ra_reasoner2.0-q5_k_s.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo darkc0de/RA_Reasoner2.0-Q5_K_S-GGUF --hf-file ra_reasoner2.0-q5_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 darkc0de/RA_Reasoner2.0-Q5_K_S-GGUF --hf-file ra_reasoner2.0-q5_k_s.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo darkc0de/RA_Reasoner2.0-Q5_K_S-GGUF --hf-file ra_reasoner2.0-q5_k_s.gguf -c 2048
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Model tree for darkc0de/RA_Reasoner2.0-Q5_K_S-GGUF
Base model
tiiuae/Falcon3-10B-Base
Finetuned
tiiuae/Falcon3-10B-Instruct
Finetuned
Daemontatox/RA_Reasoner
Finetuned
Daemontatox/RA_Reasoner2.0
Dataset used to train darkc0de/RA_Reasoner2.0-Q5_K_S-GGUF
Evaluation results
- averaged accuracy on IFEval (0-Shot)Open LLM Leaderboard53.660
- normalized accuracy on BBH (3-Shot)test set Open LLM Leaderboard43.070
- exact match on MATH Lvl 5 (4-Shot)test set Open LLM Leaderboard22.890
- acc_norm on GPQA (0-shot)Open LLM Leaderboard9.960
- acc_norm on MuSR (0-shot)Open LLM Leaderboard7.180
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard37.260