How to use from
llama.cpp
Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf roleplaiapp/SmallThinker-3B-Preview-IQ4_NL-GGUF:IQ4_NL
# Run inference directly in the terminal:
llama-cli -hf roleplaiapp/SmallThinker-3B-Preview-IQ4_NL-GGUF:IQ4_NL
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf roleplaiapp/SmallThinker-3B-Preview-IQ4_NL-GGUF:IQ4_NL
# Run inference directly in the terminal:
llama-cli -hf roleplaiapp/SmallThinker-3B-Preview-IQ4_NL-GGUF:IQ4_NL
Use 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 roleplaiapp/SmallThinker-3B-Preview-IQ4_NL-GGUF:IQ4_NL
# Run inference directly in the terminal:
./llama-cli -hf roleplaiapp/SmallThinker-3B-Preview-IQ4_NL-GGUF:IQ4_NL
Build 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 roleplaiapp/SmallThinker-3B-Preview-IQ4_NL-GGUF:IQ4_NL
# Run inference directly in the terminal:
./build/bin/llama-cli -hf roleplaiapp/SmallThinker-3B-Preview-IQ4_NL-GGUF:IQ4_NL
Use Docker
docker model run hf.co/roleplaiapp/SmallThinker-3B-Preview-IQ4_NL-GGUF:IQ4_NL
Quick Links

roleplaiapp/SmallThinker-3B-Preview-IQ4_NL-GGUF

Repo: roleplaiapp/SmallThinker-3B-Preview-IQ4_NL-GGUF
Original Model: SmallThinker-3B-Preview Organization: PowerInfer Quantized File: smallthinker-3b-preview-iq_4nl-imat.gguf Quantization: GGUF Quantization Method: IQ4_NL
Use Imatrix: True
Split Model: False

Overview

This is an imatrix GGUF IQ4_NL quantized version of SmallThinker-3B-Preview.

Quantization By

I often have idle A100 GPUs while building/testing and training the RP app, so I put them to use quantizing models. I hope the community finds these quantizations useful.

Andrew Webby @ RolePlai

Downloads last month
4
GGUF
Model size
3B params
Architecture
qwen2
Hardware compatibility
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4-bit

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Base model

Qwen/Qwen2.5-3B
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Datasets used to train roleplaiapp/SmallThinker-3B-Preview-IQ4_NL-GGUF