Text Generation
Transformers
Safetensors
English
home-assistant
phi-4
iot
function-calling
smart-home
conversational
Instructions to use TitleOS/HomePhi4_4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TitleOS/HomePhi4_4B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TitleOS/HomePhi4_4B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TitleOS/HomePhi4_4B", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use TitleOS/HomePhi4_4B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TitleOS/HomePhi4_4B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TitleOS/HomePhi4_4B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/TitleOS/HomePhi4_4B
- SGLang
How to use TitleOS/HomePhi4_4B with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "TitleOS/HomePhi4_4B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TitleOS/HomePhi4_4B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "TitleOS/HomePhi4_4B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TitleOS/HomePhi4_4B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use TitleOS/HomePhi4_4B with Docker Model Runner:
docker model run hf.co/TitleOS/HomePhi4_4B
Update README.md
Browse files
README.md
CHANGED
|
@@ -65,7 +65,10 @@ In addition, answer questions about the world, news, and general knowledge when
|
|
| 65 |
If a request appears to be an accident or otherwise doesn't make sense, reply with "Canceled".
|
| 66 |
|
| 67 |
|
| 68 |
-
Quantized Models/GGUFs:
|
|
|
|
| 69 |
Merged Model FP16: https://huggingface.co/TitleOS/HomePhi4_4B_Merged
|
|
|
|
| 70 |
Q_8: https://huggingface.co/TitleOS/HomePhi4_4B_Merged-Q8_0-GGUF
|
| 71 |
-
|
|
|
|
|
|
| 65 |
If a request appears to be an accident or otherwise doesn't make sense, reply with "Canceled".
|
| 66 |
|
| 67 |
|
| 68 |
+
## Quantized Models/GGUFs:
|
| 69 |
+
|
| 70 |
Merged Model FP16: https://huggingface.co/TitleOS/HomePhi4_4B_Merged
|
| 71 |
+
|
| 72 |
Q_8: https://huggingface.co/TitleOS/HomePhi4_4B_Merged-Q8_0-GGUF
|
| 73 |
+
|
| 74 |
+
Q4_K_M: https://huggingface.co/TitleOS/HomePhi4_4B_Merged-Q4_K_M-GGUF
|