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
```

SeaWolf-AI commited on 5 days ago

Commit

eea4d0f

verified ·

1 Parent(s): 613f399

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

Browse files

Files changed (1) hide show

config.json +51 -46

config.json CHANGED Viewed

@@ -1,47 +1,52 @@
-{
-  "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
 }

+{
+  "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"
+  }
 }