f172f7d4aa
- Introduced new skills tools: `skills_categories`, `skills_list`, and `skill_view` in `model_tools.py`, allowing for better organization and access to skill-related functionalities. - Updated `toolsets.py` to include a new `skills` toolset, providing a dedicated space for skill tools. - Enhanced `batch_runner.py` to recognize and validate skills tools during batch processing. - Added comprehensive tool definitions for skills tools, ensuring compatibility with OpenAI's expected format. - Created new shell script `test_skills_kimi.sh` for testing skills tool functionality with Kimi K2.5. - Added example skill files demonstrating the structure and usage of skills within the Hermes-Agent framework, including `SKILL.md` for example and audiocraft skills. - Improved documentation for skills tools and their integration into the existing tool framework, ensuring clarity for future development and usage.
90 lines
1.6 KiB
Markdown
90 lines
1.6 KiB
Markdown
# Performance Optimization Guide
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Maximize llama.cpp inference speed and efficiency.
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## CPU Optimization
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### Thread tuning
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```bash
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# Set threads (default: physical cores)
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./llama-cli -m model.gguf -t 8
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# For AMD Ryzen 9 7950X (16 cores, 32 threads)
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-t 16 # Best: physical cores
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# Avoid hyperthreading (slower for matrix ops)
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```
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### BLAS acceleration
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```bash
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# OpenBLAS (faster matrix ops)
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make LLAMA_OPENBLAS=1
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# BLAS gives 2-3× speedup
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```
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## GPU Offloading
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### Layer offloading
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```bash
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# Offload 35 layers to GPU (hybrid mode)
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./llama-cli -m model.gguf -ngl 35
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# Offload all layers
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./llama-cli -m model.gguf -ngl 999
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# Find optimal value:
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# Start with -ngl 999
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# If OOM, reduce by 5 until fits
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```
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### Memory usage
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```bash
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# Check VRAM usage
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nvidia-smi dmon
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# Reduce context if needed
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./llama-cli -m model.gguf -c 2048 # 2K context instead of 4K
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```
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## Batch Processing
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```bash
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# Increase batch size for throughput
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./llama-cli -m model.gguf -b 512 # Default: 512
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# Physical batch (GPU)
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--ubatch 128 # Process 128 tokens at once
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```
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## Context Management
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```bash
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# Default context (512 tokens)
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-c 512
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# Longer context (slower, more memory)
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-c 4096
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# Very long context (if model supports)
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-c 32768
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```
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## Benchmarks
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### CPU Performance (Llama 2-7B Q4_K_M)
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| Setup | Speed | Notes |
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|-------|-------|-------|
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| Apple M3 Max | 50 tok/s | Metal acceleration |
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| AMD 7950X (16c) | 35 tok/s | OpenBLAS |
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| Intel i9-13900K | 30 tok/s | AVX2 |
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### GPU Offloading (RTX 4090)
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| Layers GPU | Speed | VRAM |
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|------------|-------|------|
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| 0 (CPU only) | 30 tok/s | 0 GB |
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| 20 (hybrid) | 80 tok/s | 8 GB |
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| 35 (all) | 120 tok/s | 12 GB |
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