Instructions to use premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF",
	filename="tinyllama-1.1B-merged-F16.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF: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 premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF: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 premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF:Q4_K_M

Use Docker

docker model run hf.co/premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF:Q4_K_M

Ollama
How to use premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF with Ollama:
```
ollama run hf.co/premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF:Q4_K_M
```

Unsloth Studio

How to use premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF 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 premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF 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 premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF to start chatting

Docker Model Runner
How to use premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF with Docker Model Runner:
```
docker model run hf.co/premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF:Q4_K_M
```

Lemonade

How to use premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull premrajreddy/Home-TinyLlama-1.1B-HomeAssist-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Home-TinyLlama-1.1B-HomeAssist-GGUF-Q4_K_M

List all available models

lemonade list

premrajreddy commited on Aug 19, 2025

Commit

31ca237

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1 Parent(s): 13b049e

Create README.md

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