Instructions to use mradermacher/Orthrus-12b-v0.8-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/Orthrus-12b-v0.8-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/Orthrus-12b-v0.8-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use mradermacher/Orthrus-12b-v0.8-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/Orthrus-12b-v0.8-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf mradermacher/Orthrus-12b-v0.8-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/Orthrus-12b-v0.8-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf mradermacher/Orthrus-12b-v0.8-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/Orthrus-12b-v0.8-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf mradermacher/Orthrus-12b-v0.8-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/Orthrus-12b-v0.8-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf mradermacher/Orthrus-12b-v0.8-GGUF:Q4_K_M
Use Docker
docker model run hf.co/mradermacher/Orthrus-12b-v0.8-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use mradermacher/Orthrus-12b-v0.8-GGUF with Ollama:
ollama run hf.co/mradermacher/Orthrus-12b-v0.8-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use mradermacher/Orthrus-12b-v0.8-GGUF with Docker Model Runner:
docker model run hf.co/mradermacher/Orthrus-12b-v0.8-GGUF:Q4_K_M
- Lemonade
How to use mradermacher/Orthrus-12b-v0.8-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mradermacher/Orthrus-12b-v0.8-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Orthrus-12b-v0.8-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
File size: 1,862 Bytes
c42b175 1c67968 c42b175 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 | ---
base_model: Pyroserenus/Orthrus-12b-v0.8
language:
- en
library_name: transformers
license: cc-by-nc-4.0
quantized_by: mradermacher
tags:
- mergekit
- merge
---
## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
static quants of https://huggingface.co/Pyroserenus/Orthrus-12b-v0.8
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
## Usage
If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
more details, including on how to concatenate multi-part files.
## Provided Quants
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
| Link | Type | Size/GB | Notes |
|:-----|:-----|--------:|:------|
| [GGUF](https://huggingface.co/mradermacher/Orthrus-12b-v0.8-GGUF/resolve/main/Orthrus-12b-v0.8.Q8_0.gguf) | Q8_0 | 13.1 | fast, best quality |
Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):

And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
## FAQ / Model Request
See https://huggingface.co/mradermacher/model_requests for some answers to
questions you might have and/or if you want some other model quantized.
## Thanks
I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.
<!-- end -->
|