EmbeddedLLM / Phi-3-mini-4k-instruct-062024-int4-directml

huggingface.co
Total runs: 3
24-hour runs: 0
7-day runs: 0
30-day runs: 0
Model's Last Updated: July 19 2024
text-generation

Introduction of Phi-3-mini-4k-instruct-062024-int4-directml

Model Details of Phi-3-mini-4k-instruct-062024-int4-directml

EmbeddedLLM/Phi-3-mini-4k-instruct-062024-int4-onnx-directml

Model Summary

This model is an ONNX-optimized version of microsoft/Phi-3-mini-4k-instruct (June 2024) , designed to provide accelerated inference on a variety of hardware using ONNX Runtime(CPU and DirectML). DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning, providing GPU acceleration for a wide range of supported hardware and drivers, including AMD, Intel, NVIDIA, and Qualcomm GPUs.

ONNX Models

Here are some of the optimized configurations we have added:

  • ONNX model for int4 DirectML: ONNX model for AMD, Intel, and NVIDIA GPUs on Windows, quantized to int4 using AWQ.
Hardware Requirements

Minimum Configuration:

  • Windows: DirectX 12-capable GPU (AMD/Nvidia)
  • CPU: x86_64 / ARM64 Tested Configurations:
  • GPU: AMD Ryzen 8000 Series iGPU (DirectML)
  • CPU: AMD Ryzen CPU
Model Description
  • Developed by: Microsoft
  • Model type: ONNX
  • Language(s) (NLP): Python, C, C++
  • License: Apache License Version 2.0
  • Model Description: This model is a conversion of the Phi-3-mini-4k-instruct-062024 for ONNX Runtime inference, optimized for DirectML.
Performance Metrics
DirectML

We measured the performance of DirectML on AMD Ryzen 9 7940HS /w Radeon 78

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Runs of EmbeddedLLM Phi-3-mini-4k-instruct-062024-int4-directml on huggingface.co

3
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
0
30-day runs

More Information About Phi-3-mini-4k-instruct-062024-int4-directml huggingface.co Model

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Phi-3-mini-4k-instruct-062024-int4-directml huggingface.co

Phi-3-mini-4k-instruct-062024-int4-directml huggingface.co is an AI model on huggingface.co that provides Phi-3-mini-4k-instruct-062024-int4-directml's model effect (), which can be used instantly with this EmbeddedLLM Phi-3-mini-4k-instruct-062024-int4-directml model. huggingface.co supports a free trial of the Phi-3-mini-4k-instruct-062024-int4-directml model, and also provides paid use of the Phi-3-mini-4k-instruct-062024-int4-directml. Support call Phi-3-mini-4k-instruct-062024-int4-directml model through api, including Node.js, Python, http.

Phi-3-mini-4k-instruct-062024-int4-directml huggingface.co Url

https://huggingface.co/EmbeddedLLM/Phi-3-mini-4k-instruct-062024-int4-directml

EmbeddedLLM Phi-3-mini-4k-instruct-062024-int4-directml online free

Phi-3-mini-4k-instruct-062024-int4-directml huggingface.co is an online trial and call api platform, which integrates Phi-3-mini-4k-instruct-062024-int4-directml's modeling effects, including api services, and provides a free online trial of Phi-3-mini-4k-instruct-062024-int4-directml, you can try Phi-3-mini-4k-instruct-062024-int4-directml online for free by clicking the link below.

EmbeddedLLM Phi-3-mini-4k-instruct-062024-int4-directml online free url in huggingface.co:

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Phi-3-mini-4k-instruct-062024-int4-directml install

Phi-3-mini-4k-instruct-062024-int4-directml is an open source model from GitHub that offers a free installation service, and any user can find Phi-3-mini-4k-instruct-062024-int4-directml on GitHub to install. At the same time, huggingface.co provides the effect of Phi-3-mini-4k-instruct-062024-int4-directml install, users can directly use Phi-3-mini-4k-instruct-062024-int4-directml installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

Phi-3-mini-4k-instruct-062024-int4-directml install url in huggingface.co:

https://huggingface.co/EmbeddedLLM/Phi-3-mini-4k-instruct-062024-int4-directml

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