Instructions to use IkariDev/Athena-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use IkariDev/Athena-v2 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="IkariDev/Athena-v2")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("IkariDev/Athena-v2")
model = AutoModelForCausalLM.from_pretrained("IkariDev/Athena-v2", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use IkariDev/Athena-v2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "IkariDev/Athena-v2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "IkariDev/Athena-v2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/IkariDev/Athena-v2

SGLang

How to use IkariDev/Athena-v2 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "IkariDev/Athena-v2" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "IkariDev/Athena-v2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "IkariDev/Athena-v2" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "IkariDev/Athena-v2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use IkariDev/Athena-v2 with Docker Model Runner:
```
docker model run hf.co/IkariDev/Athena-v2
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Experimental Athena v2 model. Use Alpaca format.

Description

This repo contains fp16 files of Athena-V2.

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!

Models and loras used

Xwin-LM/Xwin-LM-13B-V0.1
Undi95/ReMM-v2.2-L2-13B
Undi95/MLewd-L2-13B-v2-3
Brouz/Slerpeno
boomerchan/Magpie-13b

[Xwin (0.30) + ReMM v2.2 (0.70)](0.45) x [[Xwin (0.40) + MLewd v2-3 (0.60)](0.80) + [Slerpeno(0.50) + Magpie-13b(0.50)](0.20)](0.55)

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.

Downloads last month: 68

Safetensors

Model size

13B params

Tensor type

F32

BF16

Model tree for IkariDev/Athena-v2

Quantizations

4 models