Instructions to use muradil211/AetherSearch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use muradil211/AetherSearch with Transformers:

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

pipe = pipeline("text-generation", model="muradil211/AetherSearch")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("muradil211/AetherSearch")
model = AutoModelForCausalLM.from_pretrained("muradil211/AetherSearch", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use muradil211/AetherSearch with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "muradil211/AetherSearch"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "muradil211/AetherSearch",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/muradil211/AetherSearch

SGLang

How to use muradil211/AetherSearch 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 "muradil211/AetherSearch" \
    --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": "muradil211/AetherSearch",
		"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 "muradil211/AetherSearch" \
        --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": "muradil211/AetherSearch",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use muradil211/AetherSearch with Docker Model Runner:
```
docker model run hf.co/muradil211/AetherSearch
```

AetherSearch / MODEL_MANIFEST.sha256

Muradil Mamat

Upload AetherSearch model release

c15eb50 6 days ago

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	424ed32fb34577a81d9b518900bbb2f4ffbf94c7a1fbfca21f8b4270da6f9c44 ./.gitattributes
	ee7977c1f891dc3ae7089798867c71a2d50895063800133eee1b6d8165acab71 ./README.md
	58b54bbe36fc752f79a24a271ef66a0a0830054b4dfad94bde757d851968060b ./added_tokens.json
	45eb13faa23e61311a8152ca6bb4c20f0a9a7455b65f34e59e55c084f5fe8eac ./config.json
	80b8ec6e7991b64763e4ff29b59a9cd2968b390d0736e0dc586585da04bad013 ./generation_config.json
	8831e4f1a044471340f7c0a83d7bd71306a5b867e95fd870f74d0c5308a904d5 ./merges.txt
	ddc905edca455e63f2d127faa00268155cee12428789b6b88680128d88a9ea3c ./model.safetensors
	76862e765266b85aa9459767e33cbaf13970f327a0e88d1c65846c2ddd3a1ecd ./special_tokens_map.json
	9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa ./tokenizer.json
	57fea41fa99fce34f91450643e48b3bfbb078c32c6831a3c06834f122c200510 ./tokenizer_config.json
	ca10d7e9fb3ed18575dd1e277a2579c16d108e32f27439684afa0e10b1440910 ./vocab.json