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
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 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/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 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 report.md with huggingface_hub
Browse files
report.md
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@@ -44,3 +44,14 @@ Memory: model buffer 4701 MiB (mmap), KV 17408 MiB @ 16k ctx (F16).
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## Files
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- results/amx_threads.jsonl: raw llama-bench samples
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- build: llama-pinned/build-amx (binaries)
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## Files
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- results/amx_threads.jsonl: raw llama-bench samples
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- build: llama-pinned/build-amx (binaries)
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## CLI measured (real generation, prompt ~19 tokens + 128 gen, 16 threads, F16 KV, FA on)
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| Build | repack | Prompt t/s (median) | Gen t/s (median) |
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| AMX-enabled | on (AMX VNNI) | 141.9 | 18.7 |
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| AMX-enabled | off (AVX-512) | 147.4 | 19.4 |
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| stock (AMX disabled) | on (CPU_REPACK) | 129.3 | 18.7 |
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| stock (AMX disabled) | off | 134.3 | 19.3 |
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Best: AMX-enabled build with repack off → 147.4 t/s prefill, 19.4 t/s decode.
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