Instructions to use enosislabs/aether-2b-cyber with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use enosislabs/aether-2b-cyber with Transformers:

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

pipe = pipeline("text-generation", model="enosislabs/aether-2b-cyber")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("enosislabs/aether-2b-cyber")
model = AutoModelForMultimodalLM.from_pretrained("enosislabs/aether-2b-cyber")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.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(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use enosislabs/aether-2b-cyber with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "enosislabs/aether-2b-cyber"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "enosislabs/aether-2b-cyber",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/enosislabs/aether-2b-cyber

SGLang

How to use enosislabs/aether-2b-cyber 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 "enosislabs/aether-2b-cyber" \
    --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": "enosislabs/aether-2b-cyber",
		"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 "enosislabs/aether-2b-cyber" \
        --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": "enosislabs/aether-2b-cyber",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use enosislabs/aether-2b-cyber with Docker Model Runner:
```
docker model run hf.co/enosislabs/aether-2b-cyber
```

aether-2b-cyber / README.md

ferxalb

Publish enosislabs-aether-2b-cyber transformers package

f25765c verified 11 days ago

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metadata

license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
base_model: Qwen/Qwen3.5-0.8B
language:
  - en
tags:
  - cybersecurity
  - conversational
  - purple-team
  - prism
  - qwen3.5
  - safetensors
model_name: enosislabs-aether-2b-cyber

EnosisLabs enosislabs-aether-2b-cyber

Generated UTC: 2026-06-21T06:52:20.705361+00:00 Source model: /checkpoints/aether-2b-20260621-0640 Brand: EnosisLabs

Canonical merged Transformers artifacts for enosislabs-aether-2b-cyber.

Derived deployment repos:

GGUF: enosislabs/aether-2b-cyber-gguf
ONNX: enosislabs/aether-2b-cyber-onnx

Variant Layout

fp16

Artifact Semantics

repository root: canonical merged Transformers model in FP16 when present.
bf16/: complete merged Transformers model converted to BF16.
artifact_manifest.json: full local packaging manifest.

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

repo_id = "enosislabs/aether-2b-cyber"
tokenizer = AutoTokenizer.from_pretrained(repo_id)
model = AutoModelForCausalLM.from_pretrained(repo_id, device_map="auto")

Usage Rider

Intended only for authorized security testing, defensive engineering, internal red-team labs, and purple-team education.