julienkay/Phi-3-mini-4k-instruct_no_cache_uint8

Model

This is a work-in-progress attempt to use a Phi-3 model with Unity Sentis.

0

13 commits

1 linked in READMEs

updated Aug 14, 2024

See the code

README

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.

custom_code
phi3
unity-sentis

julienkay/Phi-3-mini-4k-instruct_no_cache_uint8

Model

This is a work-in-progress attempt to use a Phi-3 model with Unity Sentis.

0

13 commits

1 linked in READMEs

updated Aug 14, 2024

See the code

README

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.

custom_code
phi3
unity-sentis