Instructions to use IkariDev/Athena-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IkariDev/Athena-v4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="IkariDev/Athena-v4")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("IkariDev/Athena-v4") model = AutoModelForCausalLM.from_pretrained("IkariDev/Athena-v4") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use IkariDev/Athena-v4 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "IkariDev/Athena-v4" # 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-v4", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/IkariDev/Athena-v4
- SGLang
How to use IkariDev/Athena-v4 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-v4" \ --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-v4", "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-v4" \ --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-v4", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use IkariDev/Athena-v4 with Docker Model Runner:
docker model run hf.co/IkariDev/Athena-v4
Experimental Athena v4 model. Use Alpaca format. Suitable for RP, ERP and general stuff.
I should state here that this is a HIGHLY experimental model!
Description
This repo contains fp16 files of Athena-V4.
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!
If you want your rating to be here, send me a message over on DC and ill put up a screenshot of it here. DC name is "ikaridev".
Models+loras used and recipe
- Athena-v3
- Xwin-LM/Xwin-LM-13B-V0.1
- Undi95/PsyMedRP-v1-13B
- cgato/Thespis-13b-v0.2
- jondurbin/airoboros-l2-13b-3.0
Athena-v4-tmp1 = [ Athena-v3(0.85)+Xwin-LM/Xwin-LM-13B-V0.1(0.15) ]
Athena-v4-tmp2 = [ Undi95/PsyMedRP-v1-13B(0.55)+cgato/Thespis-13b-v0.2(0.45) ]
Athena-v4-tmp3 = Athena-v4-tmp1(0.55) + Athena-v4-tmp2(0.35)
Athena-v4 = Athena-v4-tmp3 + jondurbin/airoboros-l2-13b-3.0(0.1)
Prompt template: Alpaca
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
{prompt}
### Response:
Thanks to Undi95 for providing the machine for Athena v2 and Athena v3, and giving me infos about how things work. Going forward i will use a merging server provided by a friend.
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