Instructions to use IkariDev/Athnete-13B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use IkariDev/Athnete-13B with Transformers:

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

pipe = pipeline("text-generation", model="IkariDev/Athnete-13B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("IkariDev/Athnete-13B")
model = AutoModelForCausalLM.from_pretrained("IkariDev/Athnete-13B")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use IkariDev/Athnete-13B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "IkariDev/Athnete-13B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "IkariDev/Athnete-13B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/IkariDev/Athnete-13B

SGLang

How to use IkariDev/Athnete-13B 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/Athnete-13B" \
    --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/Athnete-13B",
		"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/Athnete-13B" \
        --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/Athnete-13B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use IkariDev/Athnete-13B with Docker Model Runner:
```
docker model run hf.co/IkariDev/Athnete-13B
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Athnete model. Use Alpaca format. Suitable for RP, ERP and general stuff.

Despite the awful banner i made, this model could actually be better than raw Athena v3.

Description

This repo contains fp16 files of Athnete.

fp16 - by IkariDev

GGUF - by IkariDev

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

IkariDev/Athena-v3
Undi95/Nete-13B

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)

Downloads last month: 78

Safetensors

Model size

13B params

Tensor type

F16

Model tree for IkariDev/Athnete-13B

Quantizations

4 models