ffe47c51b5
Full security platform with web dashboard, 16 Flask blueprints, 26 modules, autonomous AI agent, WebUSB hardware support, and Archon Android companion app. Includes Hash Toolkit, debug console, anti-stalkerware shield, Metasploit/RouterSploit integration, WireGuard VPN, OSINT reconnaissance, and multi-backend LLM support. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
42 lines
1021 B
Plaintext
42 lines
1021 B
Plaintext
# AUTARCH LLM Configuration Template
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# Hardware: NVIDIA GeForce RTX 4070 Mobile (8GB VRAM)
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# Optimized for: GPU inference with good VRAM management
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#
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# This configuration balances performance and memory usage for mobile RTX 4070.
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# The 4070 Mobile has 8GB VRAM, suitable for 7B models at full precision
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# or 13B models with quantization.
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[llama]
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# GGUF Model Settings (llama.cpp)
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model_path =
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n_ctx = 8192
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n_threads = 8
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n_gpu_layers = -1
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temperature = 0.7
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top_p = 0.9
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top_k = 40
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repeat_penalty = 1.1
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max_tokens = 4096
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seed = -1
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[transformers]
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# SafeTensors Model Settings (HuggingFace)
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model_path =
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device = cuda
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torch_dtype = float16
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load_in_8bit = false
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load_in_4bit = false
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trust_remote_code = false
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max_tokens = 4096
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temperature = 0.7
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top_p = 0.9
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top_k = 40
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repetition_penalty = 1.1
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# Notes:
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# - n_gpu_layers = -1 offloads all layers to GPU
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# - For 13B+ models, enable load_in_4bit = true
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# - float16 is optimal for RTX 4070
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# - n_ctx = 8192 uses ~2GB VRAM overhead
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# - Reduce n_ctx to 4096 if running out of VRAM
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