Instructions to use mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF", dtype="auto") - llama-cpp-python
How to use mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF", filename="LocalAI-functioncall-phi-4-v0.2.IQ4_XS.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use mradermacher/LocalAI-functioncall-phi-4-v0.2-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/LocalAI-functioncall-phi-4-v0.2-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf mradermacher/LocalAI-functioncall-phi-4-v0.2-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/LocalAI-functioncall-phi-4-v0.2-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf mradermacher/LocalAI-functioncall-phi-4-v0.2-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/LocalAI-functioncall-phi-4-v0.2-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf mradermacher/LocalAI-functioncall-phi-4-v0.2-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/LocalAI-functioncall-phi-4-v0.2-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF:Q4_K_M
Use Docker
docker model run hf.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF with Ollama:
ollama run hf.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF:Q4_K_M
- Unsloth Studio
How to use mradermacher/LocalAI-functioncall-phi-4-v0.2-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/LocalAI-functioncall-phi-4-v0.2-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/LocalAI-functioncall-phi-4-v0.2-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/LocalAI-functioncall-phi-4-v0.2-GGUF to start chatting
- Docker Model Runner
How to use mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF with Docker Model Runner:
docker model run hf.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF:Q4_K_M
- Lemonade
How to use mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.LocalAI-functioncall-phi-4-v0.2-GGUF-Q4_K_M
List all available models
lemonade list
auto-patch README.md
Browse files
README.md
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static quants of https://huggingface.co/mudler/LocalAI-functioncall-phi-4-v0.2
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<!-- provided-files -->
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weighted/imatrix quants
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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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| [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.2.Q3_K_S.gguf) | Q3_K_S | 6.6 | |
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| [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.2.Q3_K_M.gguf) | Q3_K_M | 7.3 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.2.Q3_K_L.gguf) | Q3_K_L | 7.9 | |
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| [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.2.Q4_K_S.gguf) | Q4_K_S | 8.5 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.2.Q4_K_M.gguf) | Q4_K_M | 9.0 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.2.Q6_K.gguf) | Q6_K | 12.1 | very good quality |
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| [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.2.Q8_0.gguf) | Q8_0 | 15.7 | fast, best quality |
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static quants of https://huggingface.co/mudler/LocalAI-functioncall-phi-4-v0.2
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<!-- provided-files -->
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weighted/imatrix quants are available at https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-i1-GGUF
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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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| [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.2.Q3_K_S.gguf) | Q3_K_S | 6.6 | |
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| [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.2.Q3_K_M.gguf) | Q3_K_M | 7.3 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.2.Q3_K_L.gguf) | Q3_K_L | 7.9 | |
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| [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.2.IQ4_XS.gguf) | IQ4_XS | 8.2 | |
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| [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.2.Q4_K_S.gguf) | Q4_K_S | 8.5 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.2.Q4_K_M.gguf) | Q4_K_M | 9.0 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.2.Q5_K_S.gguf) | Q5_K_S | 10.3 | |
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| [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.2.Q5_K_M.gguf) | Q5_K_M | 10.5 | |
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| [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.2.Q6_K.gguf) | Q6_K | 12.1 | very good quality |
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| [GGUF](https://huggingface.co/mradermacher/LocalAI-functioncall-phi-4-v0.2-GGUF/resolve/main/LocalAI-functioncall-phi-4-v0.2.Q8_0.gguf) | Q8_0 | 15.7 | fast, best quality |
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