Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf IntelligentEstate/Tiny_Rabbit-R1.5B-Q8_0-GGUF:Q8_0# Run inference directly in the terminal:
llama-cli -hf IntelligentEstate/Tiny_Rabbit-R1.5B-Q8_0-GGUF:Q8_0Use pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf IntelligentEstate/Tiny_Rabbit-R1.5B-Q8_0-GGUF:Q8_0# Run inference directly in the terminal:
./llama-cli -hf IntelligentEstate/Tiny_Rabbit-R1.5B-Q8_0-GGUF:Q8_0Build from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf IntelligentEstate/Tiny_Rabbit-R1.5B-Q8_0-GGUF:Q8_0# Run inference directly in the terminal:
./build/bin/llama-cli -hf IntelligentEstate/Tiny_Rabbit-R1.5B-Q8_0-GGUF:Q8_0Use Docker
docker model run hf.co/IntelligentEstate/Tiny_Rabbit-R1.5B-Q8_0-GGUF:Q8_0IntelligentEstate/Tiny_Rabbit-R1-Q8_0-GGUF
This is a Complex reasoning model, it has a unique ability to reason through the incorporation of NEW information. With this model you can now choose how to introduce the new information.
Reasoning models operate within their respective Knowledge base. This is helpfull in contextualizing new complex information or introduction of new material. It is rare they exceed the reasoning knowledge base alone. This model excells when re-expressing information from the web or a RAG database. For quick use in Swarm bases this is a great little model when given proper context and instructions. Generally though it increases the knowledge base from -20% thru +10% so verify your application uasage through testing before application. The 1.5B model this is based on has reinforced mathmatical context, increasing the tool use and suprisingly it's short form writing. Enjoy and please leave feedback.
This model was converted to GGUF format from agentica-org/DeepScaleR-1.5B-Preview using llama.cpp
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.
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Base model
deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
Install from brew
# Start a local OpenAI-compatible server with a web UI: llama-server -hf IntelligentEstate/Tiny_Rabbit-R1.5B-Q8_0-GGUF:Q8_0# Run inference directly in the terminal: llama-cli -hf IntelligentEstate/Tiny_Rabbit-R1.5B-Q8_0-GGUF:Q8_0