Instructions to use IkariDev/Athena-v3-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use IkariDev/Athena-v3-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="IkariDev/Athena-v3-GGUF", filename="Athena-v3.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 IkariDev/Athena-v3-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf IkariDev/Athena-v3-GGUF:Q4_K_S # Run inference directly in the terminal: llama-cli -hf IkariDev/Athena-v3-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 IkariDev/Athena-v3-GGUF:Q4_K_S # Run inference directly in the terminal: llama-cli -hf IkariDev/Athena-v3-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 IkariDev/Athena-v3-GGUF:Q4_K_S # Run inference directly in the terminal: ./llama-cli -hf IkariDev/Athena-v3-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 IkariDev/Athena-v3-GGUF:Q4_K_S # Run inference directly in the terminal: ./build/bin/llama-cli -hf IkariDev/Athena-v3-GGUF:Q4_K_S
Use Docker
docker model run hf.co/IkariDev/Athena-v3-GGUF:Q4_K_S
- LM Studio
- Jan
- Ollama
How to use IkariDev/Athena-v3-GGUF with Ollama:
ollama run hf.co/IkariDev/Athena-v3-GGUF:Q4_K_S
- Unsloth Studio new
How to use IkariDev/Athena-v3-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 IkariDev/Athena-v3-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 IkariDev/Athena-v3-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for IkariDev/Athena-v3-GGUF to start chatting
- Docker Model Runner
How to use IkariDev/Athena-v3-GGUF with Docker Model Runner:
docker model run hf.co/IkariDev/Athena-v3-GGUF:Q4_K_S
- Lemonade
How to use IkariDev/Athena-v3-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull IkariDev/Athena-v3-GGUF:Q4_K_S
Run and chat with the model
lemonade run user.Athena-v3-GGUF-Q4_K_S
List all available models
lemonade list
Experimental Athena v3 model. Use Alpaca format. Suitable for RP, ERP and general stuff.
Description
This repo contains GGUF files of Athena-V3.
OLD(GGUF - by IkariDev+Undi95)
Ratings:
Note: I have permission of all users to upload their ratings, i DONT screenshot random reviews without asking if i can put them here!
https://snombler.neocities.org/logs#athenav3
Models and loras used
- Athena-v2
- migtissera/Synthia-13B-v1.2
- The-Face-Of-Goonery/Huginn-13b-FP16
- PygmalionAI/pygmalion-2-13b
- The-Face-Of-Goonery/LegerDemain-FP16
- chargoddard/storytime-13b
- lemonilia/LimaRP-Llama2-13B-v3-EXPERIMENT
- zattio770/120-Days-of-LORA-v2-13B
Loras: [lemonilia/LimaRP-Llama2-13B-v3-EXPERIMENT(0.65) + zattio770/120-Days-of-LORA-v2-13B(0.35)](0.3) to the final model
+ [Athena-v2(0.70) + migtissera/Synthia-13B-v1.2(0.3)](0.5)
+ [The-Face-Of-Goonery/Huginn-13b-FP16(0.85) + PygmalionAI/pygmalion-2-13b](0.15)](0.40)
+ [The-Face-Of-Goonery/LegerDemain-FP16(0.3) chargoddard/storytime-13b(0.7)](0.10)
Prompt template: Alpaca
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
{prompt}
### Response:
HUGE thanks to Undi95 for doing the merging (Recipe was my idea, he merged)
To TheBloke: please if you quant this, please include IkariDev + Undi95 in all the credits/links to the creator.
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