Instructions to use KaraKaraWarehouse/PygKiCOTlion-ggml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use KaraKaraWarehouse/PygKiCOTlion-ggml with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="KaraKaraWarehouse/PygKiCOTlion-ggml",
	filename="Pygmalion-2-13B-SuperCOTKimiko.Q5_K_M.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 KaraKaraWarehouse/PygKiCOTlion-ggml with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf KaraKaraWarehouse/PygKiCOTlion-ggml:Q5_K_M
# Run inference directly in the terminal:
llama-cli -hf KaraKaraWarehouse/PygKiCOTlion-ggml:Q5_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf KaraKaraWarehouse/PygKiCOTlion-ggml:Q5_K_M
# Run inference directly in the terminal:
llama-cli -hf KaraKaraWarehouse/PygKiCOTlion-ggml:Q5_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 KaraKaraWarehouse/PygKiCOTlion-ggml:Q5_K_M
# Run inference directly in the terminal:
./llama-cli -hf KaraKaraWarehouse/PygKiCOTlion-ggml:Q5_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 KaraKaraWarehouse/PygKiCOTlion-ggml:Q5_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf KaraKaraWarehouse/PygKiCOTlion-ggml:Q5_K_M

Use Docker

docker model run hf.co/KaraKaraWarehouse/PygKiCOTlion-ggml:Q5_K_M

LM Studio
Jan
Ollama
How to use KaraKaraWarehouse/PygKiCOTlion-ggml with Ollama:
```
ollama run hf.co/KaraKaraWarehouse/PygKiCOTlion-ggml:Q5_K_M
```

Unsloth Studio new

How to use KaraKaraWarehouse/PygKiCOTlion-ggml 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 KaraKaraWarehouse/PygKiCOTlion-ggml 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 KaraKaraWarehouse/PygKiCOTlion-ggml to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for KaraKaraWarehouse/PygKiCOTlion-ggml to start chatting

Docker Model Runner
How to use KaraKaraWarehouse/PygKiCOTlion-ggml with Docker Model Runner:
```
docker model run hf.co/KaraKaraWarehouse/PygKiCOTlion-ggml:Q5_K_M
```

Lemonade

How to use KaraKaraWarehouse/PygKiCOTlion-ggml with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull KaraKaraWarehouse/PygKiCOTlion-ggml:Q5_K_M

Run and chat with the model

lemonade run user.PygKiCOTlion-ggml-Q5_K_M

List all available models

lemonade list

Model Card for PygKiCOTlion

PygKiCOTlion is a a lora merge of Pygmalion-2-13b-SuperCOT + Kimiko v2

Model Details

Q: "Why do you do this?!"
A: Was bored.

Model Description

Developed by: KaraKaraWitch (Merge), kaiokendev (Original SuperCOT LoRA), nRuaif (Kimiko v2 LoRA), kingbri (Pygmalion 2 13b SuperCOT)
Model type: Decoder only
License: LLaMA2 (PygKiCOTlion), SuperCOT (MIT), Kimiko v2 (CC BY-NC-SA (?))
Finetuned from model [optional]: LLaMA2

Model Sources [optional]

Uses

YYMV.

Direct Use

Usage:

Since this is a merge between Pygmalion 2 13b SuperCOT and Kimiko v2, the following instruction formats should work:

Metharme:

<|system|>Your system prompt goes here.<|user|>Are you alive?<|model|>

Alpaca:

### Instruction:
Your instruction or question here.
### Response:

Bias, Risks, and Limitations

YMMV. This is untested territory.

Testing Feedbakc

TBD.

Training Details

N/A. Refer to the respective LoRa's and models.

Downloads last month: 24

GGUF

Model size

13B params

Architecture

llama

Hardware compatibility

5-bit

Inference Providers NEW

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