Text Generation
Safetensors
GGUF
English
llama
HelpingAI
Emotionally Intelligent
EQ
conversational
Eval Results (legacy)
Instructions to use HelpingAI/HelpingAI2-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use HelpingAI/HelpingAI2-9B with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="HelpingAI/HelpingAI2-9B", filename="helpingai2-9b-q5_0.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use HelpingAI/HelpingAI2-9B with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf HelpingAI/HelpingAI2-9B:Q5_0 # Run inference directly in the terminal: llama-cli -hf HelpingAI/HelpingAI2-9B:Q5_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf HelpingAI/HelpingAI2-9B:Q5_0 # Run inference directly in the terminal: llama-cli -hf HelpingAI/HelpingAI2-9B:Q5_0
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/HelpingAI2-9B:Q5_0 # Run inference directly in the terminal: ./llama-cli -hf HelpingAI/HelpingAI2-9B:Q5_0
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/HelpingAI2-9B:Q5_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf HelpingAI/HelpingAI2-9B:Q5_0
Use Docker
docker model run hf.co/HelpingAI/HelpingAI2-9B:Q5_0
- LM Studio
- Jan
- vLLM
How to use HelpingAI/HelpingAI2-9B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "HelpingAI/HelpingAI2-9B" # 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/HelpingAI2-9B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/HelpingAI/HelpingAI2-9B:Q5_0
- Ollama
How to use HelpingAI/HelpingAI2-9B with Ollama:
ollama run hf.co/HelpingAI/HelpingAI2-9B:Q5_0
- Unsloth Studio new
How to use HelpingAI/HelpingAI2-9B with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for HelpingAI/HelpingAI2-9B to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for HelpingAI/HelpingAI2-9B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for HelpingAI/HelpingAI2-9B to start chatting
- Pi new
How to use HelpingAI/HelpingAI2-9B with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf HelpingAI/HelpingAI2-9B:Q5_0
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "HelpingAI/HelpingAI2-9B:Q5_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use HelpingAI/HelpingAI2-9B with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf HelpingAI/HelpingAI2-9B:Q5_0
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default HelpingAI/HelpingAI2-9B:Q5_0
Run Hermes
hermes
- Docker Model Runner
How to use HelpingAI/HelpingAI2-9B with Docker Model Runner:
docker model run hf.co/HelpingAI/HelpingAI2-9B:Q5_0
- Lemonade
How to use HelpingAI/HelpingAI2-9B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull HelpingAI/HelpingAI2-9B:Q5_0
Run and chat with the model
lemonade run user.HelpingAI2-9B-Q5_0
List all available models
lemonade list
| { | |
| "_name_or_path": "Abhaykoul/HelpingAI2-9B", | |
| "architectures": [ | |
| "LlamaForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 128000, | |
| "eos_token_id": [ | |
| 128001, | |
| 128008, | |
| 128009 | |
| ], | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 14336, | |
| "max_position_embeddings": 131072, | |
| "mlp_bias": false, | |
| "model_type": "llama", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 36, | |
| "num_key_value_heads": 8, | |
| "pad_token_id": 128004, | |
| "pretraining_tp": 1, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": null, | |
| "rope_theta": 500000.0, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float16", | |
| "transformers_version": "4.44.0", | |
| "use_cache": true, | |
| "vocab_size": 128256 | |
| } | |