How to use from
llama.cppInstall 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:# Run inference directly in the terminal:
llama cli -hf starble-dev/mistral-doryV2-12b-gguf: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:# Run inference directly in the terminal:
./llama-cli -hf starble-dev/mistral-doryV2-12b-gguf: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:# Run inference directly in the terminal:
./build/bin/llama-cli -hf starble-dev/mistral-doryV2-12b-gguf:Use Docker
docker model run hf.co/starble-dev/mistral-doryV2-12b-gguf:Quick Links
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 |
- Downloads last month
- 415
Hardware compatibility
Log In to add your hardware
2-bit
3-bit
4-bit
5-bit
6-bit
8-bit
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Model tree for starble-dev/mistral-doryV2-12b-gguf
Base model
mistralai/Mistral-Nemo-Base-2407 Finetuned
BeaverAI/mistral-doryV2-12b
Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf starble-dev/mistral-doryV2-12b-gguf:# Run inference directly in the terminal: llama cli -hf starble-dev/mistral-doryV2-12b-gguf: