Text Generation
Transformers
Safetensors
English
qwen3_5
image-text-to-text
cybersecurity
conversational
purple-team
prism
qwen3.5
Instructions to use enosislabs/aether-2b-cyber with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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
| 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 | |
| ```python | |
| 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. | |