Instructions to use HelloSun/Experiment_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use HelloSun/Experiment_1 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 HelloSun/Experiment_1:Q4_K_M # Run inference directly in the terminal: llama cli -hf HelloSun/Experiment_1:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf HelloSun/Experiment_1:Q4_K_M # Run inference directly in the terminal: llama cli -hf HelloSun/Experiment_1:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf HelloSun/Experiment_1:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf HelloSun/Experiment_1:Q4_K_M
Use Docker
docker model run hf.co/HelloSun/Experiment_1:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use HelloSun/Experiment_1 with Ollama:
ollama run hf.co/HelloSun/Experiment_1:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use HelloSun/Experiment_1 with Docker Model Runner:
docker model run hf.co/HelloSun/Experiment_1:Q4_K_M
- Lemonade
How to use HelloSun/Experiment_1 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull HelloSun/Experiment_1:Q4_K_M
Run and chat with the model
lemonade run user.Experiment_1-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Upload opt/summary.md with huggingface_hub
Browse files- opt/summary.md +3 -1
opt/summary.md
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@@ -41,4 +41,6 @@ llama-perplexity --kl-divergence, 8 chunks x 512 tokens (4096 positions), base =
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- Shared host: absolute numbers move +-15% between time windows; every comparison above was interleaved.
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- Under heavy neighbour load the 16-thread (full-quota) runs can stall because of cgroup throttling.
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- Remaining headroom: 137 GB/s achieved vs ~185 GB/s raw read. Prefill (pp) not optimized.
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- Shared host: absolute numbers move +-15% between time windows; every comparison above was interleaved.
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- Under heavy neighbour load the 16-thread (full-quota) runs can stall because of cgroup throttling.
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- Remaining headroom: 137 GB/s achieved vs ~185 GB/s raw read. Prefill (pp) not optimized.
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- The patch is published as openpangu-vl-cpu-vnni.patch in HelloSun/openPangu-VL-7B-Q4KM-gguf (opt-in: CPU_VNNI=1).
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- Reproduced from scratch with the published build script (verify2_ab.jsonl): stock tg 15.1-15.4 vs VNNI 21.6-22.5 t/s
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(busier host window, ratio ~1.44x).
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