Autoload + onnx model and ipexllm in the model ui #25
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…ne type cpu and ipex
…ly, then ipex use the same model list for cpu and xpu hence depend on backend only and not the engine_type for the model list
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Aug 16, 2024
tjtanaa
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priority: high
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Autodownload of model for Onnxruntime engine if the repo id of model is provided instead of model path
Update the model list of Onnxruntime models and IpexLLM in the
modelui.py:Onnxruntime Model (DirectML):
EmbeddedLLM/01-ai_Yi-1.5-6b-Chat-int4-onnx-directmlEmbeddedLLM/Phi-3-medium-128k-instruct-onnx-directmlEmbeddedLLM/Phi-3-medium-4k-instruct-onnx-directmlEmbeddedLLM/Phi-3-mini-128k-instruct-onnx-directmlEmbeddedLLM/Phi-3-mini-4k-instruct-062024-int4-onnx-directmlEmbeddedLLM/Phi-3-mini-4k-instruct-onnx-directmlEmbeddedLLM/Starling-LM-7b-beta-int4-onnx-directmlEmbeddedLLM/gemma-2b-it-int4-onnx-directmlEmbeddedLLM/gemma-7b-it-int4-onnx-directmlEmbeddedLLM/llama-2-7b-chat-int4-onnx-directmlEmbeddedLLM/mistral_Mistral-7b-instruct-v0.3-int4-onnx-directmlEmbeddedLLM/openchat-3.6-8b-20240522-int4-onnx-directmlOnnxruntime Model (CPU):
EmbeddedLLM/Phi-3-mini-128k-instruct-onnx-cpu-int4-rtn-block-32EmbeddedLLM/Phi-3-mini-128k-instruct-onnx-cpu-int4-rtn-block-32-acc-level-4EmbeddedLLM/Phi-3-mini-4k-instruct-onnx-cpu-int4-rtn-block-32EmbeddedLLM/Phi-3-mini-4k-instruct-onnx-cpu-int4-rtn-block-32-acc-level-4EmbeddedLLM/mistral-7b-instruct-v0.3-onnx-cpu-int4-rtn-block32EmbeddedLLM/mistral-7b-instruct-v0.3-onnx-cpu-int4-rtn-block32-acc-level-4EmbeddedLLM/openchat-3.6-8b-20240522-onnx-cpu-int4-rtn-block32EmbeddedLLM/openchat-3.6-8b-20240522-onnx-cpu-int4-rtn-block32-acc-level-4IpexLLM Model:
(Ipex and CPU)
microsoft/Phi-3-medium-128k-instructmicrosoft/Phi-3-medium-4k-instructmicrosoft/Phi-3-mini-128k-instructmicrosoft/Phi-3-mini-4k-instructHot fixed the description of openvino backend and gpu device
Showing dropdown menu option where the user can use only base on its environment such as Ipex, DirectML or CPU.
