Instructions to use starble-dev/mistral-doryV2-12b-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use starble-dev/mistral-doryV2-12b-gguf with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("starble-dev/mistral-doryV2-12b-gguf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use starble-dev/mistral-doryV2-12b-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 starble-dev/mistral-doryV2-12b-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf starble-dev/mistral-doryV2-12b-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 starble-dev/mistral-doryV2-12b-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf starble-dev/mistral-doryV2-12b-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 starble-dev/mistral-doryV2-12b-gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf starble-dev/mistral-doryV2-12b-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 starble-dev/mistral-doryV2-12b-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf starble-dev/mistral-doryV2-12b-gguf:Q4_K_M
Use Docker
docker model run hf.co/starble-dev/mistral-doryV2-12b-gguf:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use starble-dev/mistral-doryV2-12b-gguf with Ollama:
ollama run hf.co/starble-dev/mistral-doryV2-12b-gguf:Q4_K_M
- Unsloth Studio
How to use starble-dev/mistral-doryV2-12b-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 starble-dev/mistral-doryV2-12b-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 starble-dev/mistral-doryV2-12b-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for starble-dev/mistral-doryV2-12b-gguf to start chatting
- Docker Model Runner
How to use starble-dev/mistral-doryV2-12b-gguf with Docker Model Runner:
docker model run hf.co/starble-dev/mistral-doryV2-12b-gguf:Q4_K_M
- Lemonade
How to use starble-dev/mistral-doryV2-12b-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull starble-dev/mistral-doryV2-12b-gguf:Q4_K_M
Run and chat with the model
lemonade run user.mistral-doryV2-12b-gguf-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Sampling:
Mistral-Nemo-12B is very sensitive to the temperature sampler, try values near 0.3 at first or else you will get some weird results. This is mentioned by MistralAI at their Transformers section.
In my personal testing, Flash-Attention seems to have seem weird effects with the model as well, however there is no confirmation on this.
Original Model: BeaverAI/mistral-doryV2-12b
How to Use: llama.cpp
Original Model License: Apache 2.0
Release Used: b3441
Quants
| Name | Quant Type | Size |
|---|---|---|
| mistral-doryV2-12b-Q2_K.gguf | Q2_K | 4.79 GB |
| mistral-doryV2-12b-Q3_K_S.gguf | Q3_K_S | 5.53 GB |
| mistral-doryV2-12b-Q3_K_M.gguf | Q3_K_M | 6.08 GB |
| mistral-doryV2-12b-Q3_K_L.gguf | Q3_K_L | 6.56 GB |
| mistral-doryV2-12b-Q4_K_S.gguf | Q4_K_S | 7.12 GB |
| mistral-doryV2-12b-Q4_K_M.gguf | Q4_K_M | 7.48 GB |
| mistral-doryV2-12b-Q5_K_S.gguf | Q5_K_S | 8.52 GB |
| mistral-doryV2-12b-Q5_K_M.gguf | Q5_K_M | 8.73 GB |
| mistral-doryV2-12b-Q6_K.gguf | Q6_K | 10.1 GB |
| mistral-doryV2-12b-Q8_0.gguf | Q8_0 | 13 GB |
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Model tree for starble-dev/mistral-doryV2-12b-gguf
Base model
mistralai/Mistral-Nemo-Base-2407