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--- |
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language: en |
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license: apache-2.0 |
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tags: |
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- home-assistant |
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- voice-assistant |
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- automation |
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- assistant |
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- home |
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pipeline_tag: text-generation |
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datasets: |
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- acon96/Home-Assistant-Requests |
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base_model: |
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- TinyLlama/TinyLlama-1.1B-Chat-v1.0 |
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base_model_relation: finetune |
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--- |
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# 🏠 TinyLLaMA-1.1B Home Assistant Voice Model |
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This model is a **fine-tuned version** of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0), trained with [acon96/Home-Assistant-Requests](https://huggingface.co/datasets/acon96/Home-Assistant-Requests). |
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It is designed to act as a **voice-controlled smart home assistant** that takes natural language instructions and outputs **Home Assistant commands**. |
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--- |
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## ✨ Features |
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- Converts **natural language voice commands** into Home Assistant automation calls. |
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- Produces **friendly confirmations** and **structured JSON service commands**. |
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- Lightweight (1.1B parameters) – runs efficiently on CPUs, GPUs, and via **Ollama** with quantization. |
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--- |
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## 🔧 Example Usage (Transformers) |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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tokenizer = AutoTokenizer.from_pretrained("premrajreddy/tinyllama-1.1b-home-llm") |
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model = AutoModelForCausalLM.from_pretrained("premrajreddy/tinyllama-1.1b-home-llm") |
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query = "turn on the kitchen lights" |
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inputs = tokenizer(query, return_tensors="pt") |
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outputs = model.generate(**inputs, max_new_tokens=80) |
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print(tokenizer.decode(outputs[0], skip_special_tokens=True)) |
