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

Libraries

How to use BreakFeelingAether/aetherargus with Transformers:

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

pipe = pipeline("text-generation", model="BreakFeelingAether/aetherargus")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("BreakFeelingAether/aetherargus", device_map="auto")

PEFT
How to use BreakFeelingAether/aetherargus with PEFT:
```
Task type is invalid.
```
Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use BreakFeelingAether/aetherargus with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf BreakFeelingAether/aetherargus:F16
# Run inference directly in the terminal:
llama cli -hf BreakFeelingAether/aetherargus:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf BreakFeelingAether/aetherargus:F16
# Run inference directly in the terminal:
llama cli -hf BreakFeelingAether/aetherargus:F16

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf BreakFeelingAether/aetherargus:F16
# Run inference directly in the terminal:
./llama-cli -hf BreakFeelingAether/aetherargus:F16

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf BreakFeelingAether/aetherargus:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf BreakFeelingAether/aetherargus:F16

Use Docker

docker model run hf.co/BreakFeelingAether/aetherargus:F16

LM Studio
Jan

vLLM

How to use BreakFeelingAether/aetherargus with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/BreakFeelingAether/aetherargus:F16

SGLang

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

Ollama
How to use BreakFeelingAether/aetherargus with Ollama:
```
ollama run hf.co/BreakFeelingAether/aetherargus:F16
```
Unsloth Desktop

How to use BreakFeelingAether/aetherargus with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf BreakFeelingAether/aetherargus:F16

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "BreakFeelingAether/aetherargus:F16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use BreakFeelingAether/aetherargus with Docker Model Runner:
```
docker model run hf.co/BreakFeelingAether/aetherargus:F16
```

Lemonade

How to use BreakFeelingAether/aetherargus with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull BreakFeelingAether/aetherargus:F16

Run and chat with the model

lemonade run user.aetherargus-F16

List all available models

lemonade list

Hermes Agent

How to use BreakFeelingAether/aetherargus with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf BreakFeelingAether/aetherargus:F16

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default BreakFeelingAether/aetherargus:F16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use BreakFeelingAether/aetherargus with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf BreakFeelingAether/aetherargus:F16

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "BreakFeelingAether/aetherargus:F16" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

BreakFeelingAether commited on Jul 28

Commit

db4db4e

verified ·

1 Parent(s): c187996

Upload aetherargus-merged/merge-summary.json with huggingface_hub

Browse files

Files changed (1) hide show

aetherargus-merged/merge-summary.json +93 -0

aetherargus-merged/merge-summary.json ADDED Viewed

	@@ -0,0 +1,93 @@

+{
+  "startedAt": "2026-07-28T01:34:41.219362+00:00",
+  "completedAt": "2026-07-28T01:49:47.068885+00:00",
+  "elapsedSeconds": 834.6444765830001,
+  "baseModel": "output/base-model",
+  "adapterPath": "/mnt/x/repos/Networksafe/ml/output/aetherguard-qwen-lora",
+  "outputDirectory": "/mnt/x/repos/Networksafe/ml/output/aetherguard-qwen-merged",
+  "mergeDevice": "cpu",
+  "peakObservedProcessRssGiB": 14.316944122314453,
+  "requiredFiles": {
+    "config": true,
+    "tokenizer": true,
+    "weightIndexOrSingleShard": true
+  },
+  "smokeSamples": 20,
+  "smokeMetrics": {
+    "schemaVersion": 1,
+    "generatedAt": "2026-07-28T01:49:34.385249+00:00",
+    "runName": "merged-smoke",
+    "sampleCount": 20,
+    "modelInvocationCount": 20,
+    "heuristicOnly": false,
+    "jsonSyntaxSuccessRate": 1.0,
+    "schemaValidRate": 1.0,
+    "verdictAccuracy": 0.95,
+    "maliciousPrecision": 1.0,
+    "maliciousRecall": 1.0,
+    "maliciousF1": 1.0,
+    "normalFalsePositiveRate": 0.0,
+    "normalFalsePositiveCount": 0,
+    "normalSampleCount": 14,
+    "attackFamilyMacroF1": 0.6580459770114943,
+    "recommendedActionAccuracy": 0.95,
+    "unknownUsageRate": 0.1,
+    "averageLatencyMs": 2805.1711582500047,
+    "p50LatencyMs": 2454.468293500213,
+    "p95LatencyMs": 4111.782672000348,
+    "peakGpuMemoryGiB": 2.6309828758239746,
+    "categoryBreakdown": {
+      "attack": {
+        "count": 3,
+        "verdictAccuracy": 1.0,
+        "predictedVerdicts": {
+          "malicious": 3
+        }
+      },
+      "hard_negative": {
+        "count": 7,
+        "verdictAccuracy": 1.0,
+        "predictedVerdicts": {
+          "safe": 7
+        }
+      },
+      "normal": {
+        "count": 7,
+        "verdictAccuracy": 1.0,
+        "predictedVerdicts": {
+          "safe": 7
+        }
+      },
+      "unknown": {
+        "count": 3,
+        "verdictAccuracy": 0.6666666666666666,
+        "predictedVerdicts": {
+          "safe": 1,
+          "unknown": 2
+        }
+      }
+    },
+    "familyBreakdown": {
+      "benign": {
+        "count": 14,
+        "attackFamilyAccuracy": 1.0,
+        "maliciousRecall": 0.0
+      },
+      "deserialization": {
+        "count": 2,
+        "attackFamilyAccuracy": 1.0,
+        "maliciousRecall": 1.0
+      },
+      "other": {
+        "count": 3,
+        "attackFamilyAccuracy": 0.6666666666666666,
+        "maliciousRecall": 0.0
+      },
+      "protocol_attack": {
+        "count": 1,
+        "attackFamilyAccuracy": 0.0,
+        "maliciousRecall": 1.0
+      }
+    }
+  }
+}