Instructions to use mradermacher/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use mradermacher/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-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 mradermacher/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf mradermacher/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf mradermacher/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf mradermacher/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-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/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf mradermacher/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-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/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf mradermacher/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-GGUF:Q4_K_M
Use Docker
docker model run hf.co/mradermacher/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use mradermacher/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-GGUF with Ollama:
ollama run hf.co/mradermacher/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use mradermacher/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-GGUF with Docker Model Runner:
docker model run hf.co/mradermacher/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-GGUF:Q4_K_M
- Lemonade
How to use mradermacher/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mradermacher/Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Fireball-Mistral-Nemo-Base-2407-sft-v2.2a-GGUF / Fireball-Mistral-Nemo-Base-2407-sft-v2.2a.Q5_K_M.gguf
- Xet hash:
- 8b80490cad32564a9ddb3c9b9efef1c7d6a6990cbfc27492a7765f4f321f5439
- Size of remote file:
- 8.73 GB
- SHA256:
- 09b7e74c7382b0a2ebdcb1e4163643ed2bbcdf21fba33ad9c5776680fcd25369
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