Instructions to use FINAL-Bench/Aether-6B-11Attn-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FINAL-Bench/Aether-6B-11Attn-base with Transformers:

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

pipe = pipeline("text-generation", model="FINAL-Bench/Aether-6B-11Attn-base", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("FINAL-Bench/Aether-6B-11Attn-base", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use FINAL-Bench/Aether-6B-11Attn-base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FINAL-Bench/Aether-6B-11Attn-base"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FINAL-Bench/Aether-6B-11Attn-base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/FINAL-Bench/Aether-6B-11Attn-base

SGLang

How to use FINAL-Bench/Aether-6B-11Attn-base 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 "FINAL-Bench/Aether-6B-11Attn-base" \
    --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": "FINAL-Bench/Aether-6B-11Attn-base",
		"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 "FINAL-Bench/Aether-6B-11Attn-base" \
        --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": "FINAL-Bench/Aether-6B-11Attn-base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use FINAL-Bench/Aether-6B-11Attn-base with Docker Model Runner:
```
docker model run hf.co/FINAL-Bench/Aether-6B-11Attn-base
```

SeaWolf-AI commited on Jul 20

Commit

c6ec355

verified ·

1 Parent(s): 3ae8f0f

sync Aether family cross-links

Browse files

Files changed (1) hide show

README.md +6 -0

README.md CHANGED Viewed

@@ -20,6 +20,12 @@ tags:
 # Aether-6B-11Attn
 **A 121-layer network that places 11 different sequence-mixing mechanisms on an 11x11 Latin square.**
 To our knowledge, this is the first model to integrate **11 heterogeneous sequence-mixing mechanisms** — attention, state-space, convolutional and linear families — inside a single network. Existing hybrids combine two or three (e.g. Mamba + Transformer).

 # Aether-6B-11Attn
+<!-- AETHER-FAMILY-LINKS -->
+**Aether family** — [![5Attn Base](https://img.shields.io/badge/%F0%9F%A7%AC_Aether--7B--5Attn-Fully_Open-green)](https://huggingface.co/FINAL-Bench/Aether-7B-5Attn) [![5Attn IT](https://img.shields.io/badge/%F0%9F%92%AC_Aether--7B--5Attn--it-Instruct-green)](https://huggingface.co/FINAL-Bench/Aether-7B-5Attn-it) [![7Attn Base](https://img.shields.io/badge/%F0%9F%A7%A9_Aether--7B--7Attn--base-Open_Weights-teal)](https://huggingface.co/FINAL-Bench/Aether-7B-7Attn-base) [![Checkpoints](https://img.shields.io/badge/%F0%9F%97%82%EF%B8%8F_Checkpoints-Intermediate-lightgrey)](https://huggingface.co/datasets/FINAL-Bench/Aether-7B-5Attn-checkpoints) [![Demo](https://img.shields.io/badge/%F0%9F%9A%80_Demo-Aether_Sovereign_AI-orange)](https://huggingface.co/spaces/FINAL-Bench/Aether-Sovereign-AI) [![Blog](https://img.shields.io/badge/%F0%9F%93%9D_Blog-Open_Source_LLM-yellow)](https://huggingface.co/blog/FINAL-Bench/opensource-llm) [![Collection](https://img.shields.io/badge/%F0%9F%93%9A_Collection-Aether_Foundation-blue)](https://huggingface.co/collections/FINAL-Bench/aether-foundation-model)
+<!-- /AETHER-FAMILY-LINKS -->
 **A 121-layer network that places 11 different sequence-mixing mechanisms on an 11x11 Latin square.**
 To our knowledge, this is the first model to integrate **11 heterogeneous sequence-mixing mechanisms** — attention, state-space, convolutional and linear families — inside a single network. Existing hybrids combine two or three (e.g. Mamba + Transformer).