HuggingFaceFW/fineweb-edu
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How to use appvoid/void.0 with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf appvoid/void.0 # Run inference directly in the terminal: llama cli -hf appvoid/void.0
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf appvoid/void.0 # Run inference directly in the terminal: llama cli -hf appvoid/void.0
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 appvoid/void.0 # Run inference directly in the terminal: ./build/bin/llama cli -hf appvoid/void.0
docker model run hf.co/appvoid/void.0
How to use appvoid/void.0 with Ollama:
ollama run hf.co/appvoid/void.0
How to use appvoid/void.0 with Docker Model Runner:
docker model run hf.co/appvoid/void.0
How to use appvoid/void.0 with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull appvoid/void.0
lemonade run user.void.0-{{QUANT_TAG}}lemonade list
Introducing void: our first ever language model, trained from scratch with a novel hybrid tokenizer on 300M high-quality tokens (total of 2 epochs on a B300) using 4096 as context window. Total cost was $23 dollars. 132m parameters. Future releases are expected to be published in the following weeks/months.
| Benchmark | Accuracy | Normalized |
|---|---|---|
| ARC Challenge | 25.17% | 27.22% |
| ARC Easy | 45.03% | 43.01% |
| HellaSwag | 31.57% | 35.77% |
| PIQA | 61.15% | 60.12% |
| WinoGrande | 53.12% | β |
| ArithMark | 35.20% | 35.20% |
Disclaimer: Even though the model is based on gemma 3 architecture, the tokenizer is different so you might need to wait until this model can be added to llama.cpp
ollama run hf.co/appvoid/void.0