Instructions to use robloxianer/babble 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 robloxianer/babble 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 robloxianer/babble:F32 # Run inference directly in the terminal: llama cli -hf robloxianer/babble:F32
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf robloxianer/babble:F32 # Run inference directly in the terminal: llama cli -hf robloxianer/babble:F32
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 robloxianer/babble:F32 # Run inference directly in the terminal: ./llama-cli -hf robloxianer/babble:F32
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 robloxianer/babble:F32 # Run inference directly in the terminal: ./build/bin/llama-cli -hf robloxianer/babble:F32
Use Docker
docker model run hf.co/robloxianer/babble:F32
- LM Studio
- Jan
- vLLM
How to use robloxianer/babble with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "robloxianer/babble" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "robloxianer/babble", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/robloxianer/babble:F32
- Ollama
How to use robloxianer/babble with Ollama:
ollama run hf.co/robloxianer/babble:F32
- Unsloth Desktop
- Docker Model Runner
How to use robloxianer/babble with Docker Model Runner:
docker model run hf.co/robloxianer/babble:F32
- Lemonade
How to use robloxianer/babble with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull robloxianer/babble:F32
Run and chat with the model
lemonade run user.babble-F32
List all available models
lemonade list
- Atomic Chat
Babble
A family of 5 tiny character-level GPTs trained from scratch on the same data (FineWeb-Edu + everyday conversations). They ramble. That's the point.
| Model | Params | Layers | d_model | Context | Val loss |
|---|---|---|---|---|---|
| Micro | 0.11M | 2 | 64 | 64 | 1.699 |
| Tiny | 0.82M | 4 | 128 | 128 | 1.388 |
| Small | 2.74M | 6 | 192 | 256 | 1.264 |
| Medium | 10.78M | 6 | 384 | 256 | 1.167 |
| Bigish | 19.47M | 8 | 448 | 256 | 1.18 |
Each model lives in its own subfolder with its own README (model card), the PyTorch weights (.pt) and a GGUF (.gguf).
- Training / chat / export code:
chiken_sandwich.py(one file does it all) - Chat with all models at once:
python chiken_sandwich.py chat - Do not trust the output. They are toys.
- Downloads last month
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Hardware compatibility
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32-bit