Text Generation
Transformers
Safetensors
English
Korean
aether_v2_11attn
aether
open-weights
heterogeneous-attention
mixture-of-experts
mamba2
state-space-model
hyena
mla
korean
vidraft
custom_code
Instructions to use FINAL-Bench/Aether-6B-11Attn-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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)# pip install -U transformers accelerate # 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
Commit History
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remove oheng/오행 references (pass 2)
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remove oheng/오행 references (pass 2)
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remove oheng/오행 references (pass 2)
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remove oheng/오행 references (pass 2)
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remove oheng/ohaeng references — neutral naming
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remove oheng/ohaeng references — neutral naming
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remove oheng/ohaeng references — neutral naming
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remove oheng/ohaeng references — neutral naming
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remove oheng/ohaeng references — neutral naming
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fix: restore YAML frontmatter (CRLF double-conversion broke metadata)
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docs: add 'which Aether model should I use?' comparison across the family
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docs: loading now works with AutoModelForCausalLM + trust_remote_code
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fix: make model loadable via AutoModelForCausalLM (add auto_map, flatten module files to repo root, inherit GenerationMixin)
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fix: make model loadable via AutoModelForCausalLM (add auto_map, flatten module files to repo root, inherit GenerationMixin)
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fix: make model loadable via AutoModelForCausalLM (add auto_map, flatten module files to repo root, inherit GenerationMixin)
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fix: make model loadable via AutoModelForCausalLM (add auto_map, flatten module files to repo root, inherit GenerationMixin)
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fix: make model loadable via AutoModelForCausalLM (add auto_map, flatten module files to repo root, inherit GenerationMixin)
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fix: make model loadable via AutoModelForCausalLM (add auto_map, flatten module files to repo root, inherit GenerationMixin)
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fix: make model loadable via AutoModelForCausalLM (add auto_map, flatten module files to repo root, inherit GenerationMixin)
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fix: make model loadable via AutoModelForCausalLM (add auto_map, flatten module files to repo root, inherit GenerationMixin)
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fix: make model loadable via AutoModelForCausalLM (add auto_map, flatten module files to repo root, inherit GenerationMixin)
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state training status: mid-training checkpoint, will update on completion
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document measured generation behaviour
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embed Latin-square layer map in card
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add Latin-square layer map
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sync Aether family cross-links
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remove working backup file
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Aether-6B-11Attn (open weights) — 11 sequence-mixing mechanisms on an 11x11 Latin square
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initial commit
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