Instructions to use smashingtags/nova-talker-2b 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 smashingtags/nova-talker-2b 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 smashingtags/nova-talker-2b:Q4_K_M # Run inference directly in the terminal: llama cli -hf smashingtags/nova-talker-2b:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf smashingtags/nova-talker-2b:Q4_K_M # Run inference directly in the terminal: llama cli -hf smashingtags/nova-talker-2b: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 smashingtags/nova-talker-2b:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf smashingtags/nova-talker-2b: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 smashingtags/nova-talker-2b:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf smashingtags/nova-talker-2b:Q4_K_M
Use Docker
docker model run hf.co/smashingtags/nova-talker-2b:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use smashingtags/nova-talker-2b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "smashingtags/nova-talker-2b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "smashingtags/nova-talker-2b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/smashingtags/nova-talker-2b:Q4_K_M
- Ollama
How to use smashingtags/nova-talker-2b with Ollama:
ollama run hf.co/smashingtags/nova-talker-2b:Q4_K_M
- Unsloth Studio
How to use smashingtags/nova-talker-2b 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 smashingtags/nova-talker-2b 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 smashingtags/nova-talker-2b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for smashingtags/nova-talker-2b to start chatting
- Docker Model Runner
How to use smashingtags/nova-talker-2b with Docker Model Runner:
docker model run hf.co/smashingtags/nova-talker-2b:Q4_K_M
- Lemonade
How to use smashingtags/nova-talker-2b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull smashingtags/nova-talker-2b:Q4_K_M
Run and chat with the model
lemonade run user.nova-talker-2b-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Upload README.md with huggingface_hub
Browse files
README.md
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---
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license: apache-2.0
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base_model: google/gemma-2-2b-it
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tags:
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- eightly
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- nova
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- gguf
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- gemma2
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pipeline_tag: text-generation
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---
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# Nova Talker 2B
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**Nova Talker 2B** is the default conversational voice for [Eight.ly OS](https://eight.ly)'s
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built-in AI assistant, **Nova**. It is **Google Gemma 2 2B** (instruction-tuned), quantized to
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`Q4_K_M` (~1.6 GB), re-hosted here so an Eight.ly OS install pulls the whole Nova stack from a
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single source it controls — no dependency on the public Ollama registry.
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## Role in Nova
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Nova is **router-in-front**: a single hidden tool router — [Nova Router 1.5B](https://huggingface.co/smashingtags/nova-router-1.5b)
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(Qwen2.5-Coder 1.5B, 99% tool-pick accuracy) — decides *which* NAS action to run for **every**
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talker. The talker's only job is to write the natural-language reply from the tool's real result.
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Nova Talker 2B is the smallest, fastest talker and the default installed on first boot; it runs on
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any CPU or GPU.
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| Talker | Base | Size | Role |
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|--------|------|------|------|
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| **Nova Talker 2B** (this repo) | Gemma 2 2B | 1.6 GB | Default voice |
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| [Nova Talker 4B](https://huggingface.co/smashingtags/nova-talker-4b) | Qwen 3 4B | 2.4 GB | Optional, richer wording |
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| Nova Talker 12B | Gemma 4 12B | 7.0 GB | Premium, GPU-only, experimental |
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## License
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Apache-2.0. Gemma is distributed under Apache-2.0 (https://ai.google.dev/gemma/apache_2).
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