Instructions to use Undi95/UndiMix-v2-13b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Undi95/UndiMix-v2-13b-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Undi95/UndiMix-v2-13b-GGUF",
	filename="UndiMix-v2-13b.q4_K_S.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use Undi95/UndiMix-v2-13b-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Undi95/UndiMix-v2-13b-GGUF:Q4_K_S
# Run inference directly in the terminal:
llama-cli -hf Undi95/UndiMix-v2-13b-GGUF:Q4_K_S

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Undi95/UndiMix-v2-13b-GGUF:Q4_K_S
# Run inference directly in the terminal:
llama-cli -hf Undi95/UndiMix-v2-13b-GGUF:Q4_K_S

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 Undi95/UndiMix-v2-13b-GGUF:Q4_K_S
# Run inference directly in the terminal:
./llama-cli -hf Undi95/UndiMix-v2-13b-GGUF:Q4_K_S

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 Undi95/UndiMix-v2-13b-GGUF:Q4_K_S
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Undi95/UndiMix-v2-13b-GGUF:Q4_K_S

Use Docker

docker model run hf.co/Undi95/UndiMix-v2-13b-GGUF:Q4_K_S

LM Studio
Jan
Ollama
How to use Undi95/UndiMix-v2-13b-GGUF with Ollama:
```
ollama run hf.co/Undi95/UndiMix-v2-13b-GGUF:Q4_K_S
```

Unsloth Studio new

How to use Undi95/UndiMix-v2-13b-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 Undi95/UndiMix-v2-13b-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 Undi95/UndiMix-v2-13b-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Undi95/UndiMix-v2-13b-GGUF to start chatting

Docker Model Runner
How to use Undi95/UndiMix-v2-13b-GGUF with Docker Model Runner:
```
docker model run hf.co/Undi95/UndiMix-v2-13b-GGUF:Q4_K_S
```

Lemonade

How to use Undi95/UndiMix-v2-13b-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Undi95/UndiMix-v2-13b-GGUF:Q4_K_S

Run and chat with the model

lemonade run user.UndiMix-v2-13b-GGUF-Q4_K_S

List all available models

lemonade list

This model speak way more than the v1, be warned.

Command used :

python ties_merge.py TheBloke/Llama-2-13B-fp16 ./UndiMix-v2-13b  --merge jondurbin/airoboros-l2-13b-2.1 --density 0.10 --merge IkariDev/Athena-v1 --density 0.10 --merge Undi95/UndiMix-v1-13b --density 0.80 --cuda

Testing around²...

Description

This repo contains GGUF files (Q4_K_S and Q5_K_M) of my personal mix : "UndiMix-v2".

It can be hot, serious, playful, and can use emoji thanks to llama-2-13b-chat-limarp-v2-merged.

Models used

TheBloke/Llama-2-13B-fp16 (base)
Undi95/MythoMax-L2-Kimiko-v2-13b (0.33)
The-Face-Of-Goonery/Huginn-13b-v1.2 (0.33)
Doctor-Shotgun/llama-2-13b-chat-limarp-v2-merged (0.33)
====REMIX====
jondurbin/airoboros-l2-13b-2.1 (0.10)
IkariDev/Athena-v1 (0.10)
UndiMix-v1-13b (0.80)

Prompt template: Alpaca

Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
{prompt}

### Response:

Special thanks to Sushi kek

Downloads last month: 11

GGUF

Model size

13B params

Architecture

llama

Hardware compatibility

4-bit

5-bit

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support