Instructions to use mradermacher/ReasonSQL-4B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/ReasonSQL-4B-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/ReasonSQL-4B-GGUF", dtype="auto") - llama-cpp-python
How to use mradermacher/ReasonSQL-4B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="mradermacher/ReasonSQL-4B-GGUF", filename="ReasonSQL-4B.IQ4_XS.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use mradermacher/ReasonSQL-4B-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf mradermacher/ReasonSQL-4B-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf mradermacher/ReasonSQL-4B-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf mradermacher/ReasonSQL-4B-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf mradermacher/ReasonSQL-4B-GGUF:Q4_K_M
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 mradermacher/ReasonSQL-4B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf mradermacher/ReasonSQL-4B-GGUF:Q4_K_M
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 mradermacher/ReasonSQL-4B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf mradermacher/ReasonSQL-4B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/mradermacher/ReasonSQL-4B-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use mradermacher/ReasonSQL-4B-GGUF with Ollama:
ollama run hf.co/mradermacher/ReasonSQL-4B-GGUF:Q4_K_M
- Unsloth Studio new
How to use mradermacher/ReasonSQL-4B-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for mradermacher/ReasonSQL-4B-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for mradermacher/ReasonSQL-4B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for mradermacher/ReasonSQL-4B-GGUF to start chatting
- Pi new
How to use mradermacher/ReasonSQL-4B-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf mradermacher/ReasonSQL-4B-GGUF:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "mradermacher/ReasonSQL-4B-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use mradermacher/ReasonSQL-4B-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf mradermacher/ReasonSQL-4B-GGUF:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default mradermacher/ReasonSQL-4B-GGUF:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use mradermacher/ReasonSQL-4B-GGUF with Docker Model Runner:
docker model run hf.co/mradermacher/ReasonSQL-4B-GGUF:Q4_K_M
- Lemonade
How to use mradermacher/ReasonSQL-4B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mradermacher/ReasonSQL-4B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.ReasonSQL-4B-GGUF-Q4_K_M
List all available models
lemonade list
auto-patch README.md
Browse files
README.md
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<!-- ### quantize_version: 2 -->
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<!-- ### output_tensor_quantised: 1 -->
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<!-- ### convert_type: hf -->
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<!-- ### quants_skip: -->
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<!-- ### skip_mmproj: -->
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static quants of https://huggingface.co/craterlabs/ReasonSQL-4B
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---
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base_model: craterlabs/ReasonSQL-4B
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datasets:
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- prem-research/birdbench
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language:
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- en
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library_name: transformers
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license: cc-by-4.0
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mradermacher:
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readme_rev: 1
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quantized_by: mradermacher
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---
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## About
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<!-- ### quantize_version: 2 -->
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<!-- ### output_tensor_quantised: 1 -->
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<!-- ### convert_type: hf -->
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<!-- ### quants_skip: -->
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<!-- ### skip_mmproj: -->
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static quants of https://huggingface.co/craterlabs/ReasonSQL-4B
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<!-- provided-files -->
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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#ReasonSQL-4B-GGUF).***
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weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
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## Usage
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If you are unsure how to use GGUF files, refer to one of [TheBloke's
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READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
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more details, including on how to concatenate multi-part files.
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## Provided Quants
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(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
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| Link | Type | Size/GB | Notes |
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|:-----|:-----|--------:|:------|
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| [GGUF](https://huggingface.co/mradermacher/ReasonSQL-4B-GGUF/resolve/main/ReasonSQL-4B.Q2_K.gguf) | Q2_K | 1.8 | |
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| [GGUF](https://huggingface.co/mradermacher/ReasonSQL-4B-GGUF/resolve/main/ReasonSQL-4B.Q3_K_S.gguf) | Q3_K_S | 2.0 | |
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| [GGUF](https://huggingface.co/mradermacher/ReasonSQL-4B-GGUF/resolve/main/ReasonSQL-4B.Q3_K_M.gguf) | Q3_K_M | 2.2 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/ReasonSQL-4B-GGUF/resolve/main/ReasonSQL-4B.Q3_K_L.gguf) | Q3_K_L | 2.3 | |
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| [GGUF](https://huggingface.co/mradermacher/ReasonSQL-4B-GGUF/resolve/main/ReasonSQL-4B.IQ4_XS.gguf) | IQ4_XS | 2.4 | |
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| [GGUF](https://huggingface.co/mradermacher/ReasonSQL-4B-GGUF/resolve/main/ReasonSQL-4B.Q4_K_S.gguf) | Q4_K_S | 2.5 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/ReasonSQL-4B-GGUF/resolve/main/ReasonSQL-4B.Q4_K_M.gguf) | Q4_K_M | 2.6 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/ReasonSQL-4B-GGUF/resolve/main/ReasonSQL-4B.Q5_K_S.gguf) | Q5_K_S | 2.9 | |
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| [GGUF](https://huggingface.co/mradermacher/ReasonSQL-4B-GGUF/resolve/main/ReasonSQL-4B.Q5_K_M.gguf) | Q5_K_M | 3.0 | |
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| [GGUF](https://huggingface.co/mradermacher/ReasonSQL-4B-GGUF/resolve/main/ReasonSQL-4B.Q6_K.gguf) | Q6_K | 3.4 | very good quality |
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| [GGUF](https://huggingface.co/mradermacher/ReasonSQL-4B-GGUF/resolve/main/ReasonSQL-4B.Q8_0.gguf) | Q8_0 | 4.4 | fast, best quality |
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| [GGUF](https://huggingface.co/mradermacher/ReasonSQL-4B-GGUF/resolve/main/ReasonSQL-4B.f16.gguf) | f16 | 8.2 | 16 bpw, overkill |
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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types (lower is better):
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And here are Artefact2's thoughts on the matter:
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https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
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## FAQ / Model Request
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See https://huggingface.co/mradermacher/model_requests for some answers to
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questions you might have and/or if you want some other model quantized.
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## Thanks
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I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
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me use its servers and providing upgrades to my workstation to enable
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this work in my free time.
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<!-- end -->
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