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
File size: 1,112 Bytes
84074f3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | 0.00.362.534 W load: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect
0.10.078.480 I cmn init: llama threadpool init, n_threads = 16
0.10.103.754 W load_hparams: Qwen-VL models require at minimum 1024 image tokens to function correctly on grounding tasks
0.10.103.757 W load_hparams: if you encounter problems with accuracy, try adding --image-min-tokens 1024
0.10.103.758 W load_hparams: more info: https://github.com/ggml-org/llama.cpp/issues/16842
0.10.849.878 I mtmd_cli_context: chat template example:
[unused9]系统:You are a helpful assistant[unused10][unused9]用户:Hello[unused10][unused9]助手:Hi there[unused10][unused9]用户:How are you?[unused10][unused9]助手:
0.10.849.883 I main: loading model: ./openpangu-vl-artifacts/openPangu-VL-7B-Q4_K_M.gguf
0.10.849.982 W WARN: This is an experimental CLI for testing multimodal capability.
0.10.849.983 W For normal use cases, please use the standard llama-cli
0.11.297.560 I encoding mtmd batch, n_chunks = 1 (done = 1, total = 3)
4.00.711.965 I mtmd batch encoding done in 229415 ms
The
|