Instructions to use mradermacher/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF", dtype="auto") - llama-cpp-python
How to use mradermacher/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="mradermacher/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF", filename="M1NDB0T-0M3G4-23B-Mistral-Small-2504.i1-IQ1_M.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/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-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/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf mradermacher/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-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/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf mradermacher/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-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/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf mradermacher/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-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/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf mradermacher/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF:Q4_K_M
Use Docker
docker model run hf.co/mradermacher/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use mradermacher/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF with Ollama:
ollama run hf.co/mradermacher/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF:Q4_K_M
- Unsloth Studio new
How to use mradermacher/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-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/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-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/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-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/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF to start chatting
- Docker Model Runner
How to use mradermacher/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF with Docker Model Runner:
docker model run hf.co/mradermacher/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF:Q4_K_M
- Lemonade
How to use mradermacher/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mradermacher/M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.M1NDB0T-0M3G4-23B-Mistral-Small-2504-i1-GGUF-Q4_K_M
List all available models
lemonade list
- Xet hash:
- 8d7f3bb2f169b7bb0ef55311c0893f4ce5ec0dccc148690c4b308365870268e4
- Size of remote file:
- 12.4 GB
- SHA256:
- 9a690bb46c773b03b4acea0d1baa83151f9140d5921f82983205defd58229243
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