Instructions to use FINAL-Bench/Aether-7B-5Attn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FINAL-Bench/Aether-7B-5Attn with Transformers:

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

pipe = pipeline("text-generation", model="FINAL-Bench/Aether-7B-5Attn", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("FINAL-Bench/Aether-7B-5Attn", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use FINAL-Bench/Aether-7B-5Attn with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FINAL-Bench/Aether-7B-5Attn"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FINAL-Bench/Aether-7B-5Attn",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/FINAL-Bench/Aether-7B-5Attn

SGLang

How to use FINAL-Bench/Aether-7B-5Attn 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-7B-5Attn" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FINAL-Bench/Aether-7B-5Attn",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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-7B-5Attn" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FINAL-Bench/Aether-7B-5Attn",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use FINAL-Bench/Aether-7B-5Attn with Docker Model Runner:
```
docker model run hf.co/FINAL-Bench/Aether-7B-5Attn
```

Aether-7B-5Attn / config.json

SeaWolf-AI

fix: make model loadable via AutoModelForCausalLM (add auto_map, flatten module files to repo root, inherit GenerationMixin)

eea4d0f verified 9 days ago

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	{
	"vocab_size": 151936,
	"hidden_size": 2048,
	"intermediate_size": 6144,
	"num_hidden_layers": 49,
	"num_attention_heads": 16,
	"num_key_value_heads": 4,
	"head_dim": 128,
	"attention_dropout": 0.0,
	"sliding_window_size": 512,
	"compress_block_size": 16,
	"num_experts": 25,
	"num_experts_per_tok": 7,
	"expert_intermediate_size": 640,
	"use_shared_expert": true,
	"router_aux_loss_coef": 0.001,
	"max_position_embeddings": 4096,
	"rope_theta": 10000.0,
	"rms_norm_eps": 1e-06,
	"hidden_act": "silu",
	"initializer_range": 0.02,
	"use_cache": false,
	"output_router_logits": true,
	"return_dict": true,
	"output_hidden_states": false,
	"dtype": "bfloat16",
	"chunk_size_feed_forward": 0,
	"is_encoder_decoder": false,
	"architectures": [
	"AETHERV27wayForCausalLM"
	],
	"id2label": {
	"0": "LABEL_0",
	"1": "LABEL_1"
	},
	"label2id": {
	"LABEL_0": 0,
	"LABEL_1": 1
	},
	"problem_type": null,
	"_name_or_path": "",
	"transformers_version": "5.3.0",
	"pad_token_id": 151643,
	"tie_word_embeddings": false,
	"model_type": "aether_v2_7way",
	"output_attentions": false,
	"auto_map": {
	"AutoConfig": "configuration_aether_v2_7way.AETHERV27wayConfig",
	"AutoModelForCausalLM": "modeling_aether_v2_7way.AETHERV27wayForCausalLM",
	"AutoModel": "modeling_aether_v2_7way.AETHERV27wayModel"
	}
	}