Instructions to use HelpingAI/HelpingAI2-6B 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 HelpingAI/HelpingAI2-6B 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 HelpingAI/HelpingAI2-6B:Q4_K_M # Run inference directly in the terminal: llama cli -hf HelpingAI/HelpingAI2-6B:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf HelpingAI/HelpingAI2-6B:Q4_K_M # Run inference directly in the terminal: llama cli -hf HelpingAI/HelpingAI2-6B: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 HelpingAI/HelpingAI2-6B:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf HelpingAI/HelpingAI2-6B: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 HelpingAI/HelpingAI2-6B:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf HelpingAI/HelpingAI2-6B:Q4_K_M
Use Docker
docker model run hf.co/HelpingAI/HelpingAI2-6B:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use HelpingAI/HelpingAI2-6B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "HelpingAI/HelpingAI2-6B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "HelpingAI/HelpingAI2-6B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/HelpingAI/HelpingAI2-6B:Q4_K_M
- Ollama
How to use HelpingAI/HelpingAI2-6B with Ollama:
ollama run hf.co/HelpingAI/HelpingAI2-6B:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use HelpingAI/HelpingAI2-6B with Docker Model Runner:
docker model run hf.co/HelpingAI/HelpingAI2-6B:Q4_K_M
- Lemonade
How to use HelpingAI/HelpingAI2-6B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull HelpingAI/HelpingAI2-6B:Q4_K_M
Run and chat with the model
lemonade run user.HelpingAI2-6B-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download generation_config.json from HelpingAI/HelpingAI2-6B: direct link, hf CLI and curl.
- Browser
- Download file 121 Bytes
-
https://huggingface.co/HelpingAI/HelpingAI2-6B/resolve/main/generation_config.json
- Command line
-
hf download hf://HelpingAI/HelpingAI2-6B/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/HelpingAI/HelpingAI2-6B/resolve/main/generation_config.json
121 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 128000, | |
| "eos_token_id": 128001, | |
| "transformers_version": "4.43.3" | |
| } | |