Text Generation
Transformers
GGUF
Safetensors
English
llama-cpp
SmallThinker-3B
Q6_K
3b
SmallThinker
qwen
PowerInfer
code
math
chat
roleplay
nlp
conversational
Instructions to use roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF:Q6_K # Run inference directly in the terminal: llama cli -hf roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF:Q6_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF:Q6_K # Run inference directly in the terminal: llama cli -hf roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF:Q6_K
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-Q6_K-GGUF:Q6_K # Run inference directly in the terminal: ./llama-cli -hf roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF:Q6_K
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-Q6_K-GGUF:Q6_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF:Q6_K
Use Docker
docker model run hf.co/roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF:Q6_K
- LM Studio
- Jan
- vLLM
How to use roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF:Q6_K
- SGLang
How to use roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF with Ollama:
ollama run hf.co/roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF:Q6_K
- Unsloth Desktop
- Docker Model Runner
How to use roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF with Docker Model Runner:
docker model run hf.co/roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF:Q6_K
- Lemonade
How to use roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF:Q6_K
Run and chat with the model
lemonade run user.SmallThinker-3B-Preview-Q6_K-GGUF-Q6_K
List all available models
lemonade list
- Atomic Chat
Upload README.md with huggingface_hub
Browse files
README.md
ADDED
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---
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datasets:
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- PowerInfer/QWQ-LONGCOT-500K
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- PowerInfer/LONGCOT-Refine-500K
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base_model:
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- Qwen/Qwen2.5-3B-Instruct
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pipeline_tag: text-generation
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language:
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- en
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library_name: transformers
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tags:
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- llama-cpp
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- SmallThinker-3B
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- gguf
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- Q6_K
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- 3b
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- SmallThinker
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- qwen
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- llama-cpp
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- PowerInfer
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- code
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- math
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- chat
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- roleplay
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- text-generation
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- safetensors
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- nlp
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- code
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---
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# roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF
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**Repo:** `roleplaiapp/SmallThinker-3B-Preview-Q6_K-GGUF`
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**Original Model:** `SmallThinker-3B`
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**Organization:** `PowerInfer`
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**Quantized File:** `smallthinker-3b-preview-q6_k.gguf`
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**Quantization:** `GGUF`
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**Quantization Method:** `Q6_K`
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**Use Imatrix:** `False`
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**Split Model:** `False`
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## Overview
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This is an GGUF Q6_K quantized version of [SmallThinker-3B](https://huggingface.co/PowerInfer/SmallThinker-3B-Preview).
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## Quantization By
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I often have idle A100 GPUs while building/testing and training the RP app, so I put them to use quantizing models.
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I hope the community finds these quantizations useful.
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Andrew Webby @ [RolePlai](https://roleplai.app/)
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