How to use from
llama.cpp
Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf KaraKaraWarehouse/MythaKiCOTlion-v2-ggml:
# Run inference directly in the terminal:
llama-cli -hf KaraKaraWarehouse/MythaKiCOTlion-v2-ggml:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf KaraKaraWarehouse/MythaKiCOTlion-v2-ggml:
# Run inference directly in the terminal:
llama-cli -hf KaraKaraWarehouse/MythaKiCOTlion-v2-ggml:
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/MythaKiCOTlion-v2-ggml:
# Run inference directly in the terminal:
./llama-cli -hf KaraKaraWarehouse/MythaKiCOTlion-v2-ggml:
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/MythaKiCOTlion-v2-ggml:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf KaraKaraWarehouse/MythaKiCOTlion-v2-ggml:
Use Docker
docker model run hf.co/KaraKaraWarehouse/MythaKiCOTlion-v2-ggml:
Quick Links

Model Card for MythaKiCOTlion

MythaKiCOTlion is a a lora merge of Mythalion 13B + (SuperCOT + Kimiko v2)

Model Details

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

Model Description

  • Developed by: KaraKaraWitch (Merge), kaiokendev (SuperCOT LoRA), nRuaif (Kimiko v2 LoRA)
  • Model type: Decoder only
  • License: LLaMA2 (MythaKiCOTlion), SuperCOT (MIT), Kimiko v1 (CC BY-NC-SA (?))
  • Finetuned from model [optional]: LLaMA2

Model Sources [optional]

Uses

YYMV.

Direct Use

Usage:

Since this is a merge between Mythalion 13B, SuperCOT-LoRA 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

  • The model appears to still suffers from Mythalion annoyances.
  • Which is to be expected, I'm thinking SuperCOT + Pyg2 Might be the way to go. Guess that's gonna be my next step.

Thanks to Trappu for the preliminary Feedback!

Training Details

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

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Model size
13B params
Architecture
llama
Hardware compatibility
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