Instructions to use julienkay/Phi-3-mini-4k-instruct_no_cache_uint8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- unity-sentis
How to use julienkay/Phi-3-mini-4k-instruct_no_cache_uint8 with unity-sentis:
string modelName = "[Your model name here].sentis"; Model model = ModelLoader.Load(Application.streamingAssetsPath + "/" + modelName); IWorker engine = WorkerFactory.CreateWorker(BackendType.GPUCompute, model); // Please see provided C# file for more details
- Notebooks
- Google Colab
- Kaggle
This is a work-in-progress attempt to use a Phi-3 model with Unity Sentis.
It's the microsoft/Phi-3-mini-4k-instruct model converted to .onnx via optimum:
from optimum.onnxruntime import ORTModelForCausalLM
model_id = "microsoft/Phi-3-mini-4k-instruct"
model = ORTModelForCausalLM.from_pretrained(model_id, use_cache = False, use_io_binding=False, export=True, trust_remote_code=True, cache_dir=".")
model.save_pretrained("phi3_onnx_no_cache/")
Then quantized to a Uint8 .sentis model file using Sentis v1.6.0-pre.1
Usage will be possible with the com.doji.transformers library, but support for LLMs is not officially released yet.
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