AshScholar/r1m-Q4_K_M-GGUF
This model was converted to GGUF format from AshScholar/r1m using llama.cpp via the ggml.ai's GGUF-my-repo space.
About Model
This model was finetuned from Qwen2.5-1M on data from DeepSeek R1. This model uses CoT, and also decides when or when not to use CoT. Credits to Rombo Org for the curated dataset from R1. r1m has a one million token context and near R1 performance.
Specs
7 billion parameters 1 million token context Utilizes tokens.
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 AshScholar/r1m-Q4_K_M-GGUF --hf-file r1m-q4_k_m.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo AshScholar/r1m-Q4_K_M-GGUF --hf-file r1m-q4_k_m.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 AshScholar/r1m-Q4_K_M-GGUF --hf-file r1m-q4_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo AshScholar/r1m-Q4_K_M-GGUF --hf-file r1m-q4_k_m.gguf -c 2048
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