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@abukhoy abukhoy commented Nov 17, 2025

This feature adds support for exporting a proxy model, which disables the Embedding Layer and LM Head of a causal model.

Set enable_proxy = True to export the proxy model.
Set write_io = True to save input/output files during the generation stage.

Refer to the example script for implementation details.

Testing

Will update soon.

Signed-off-by: Abukhoyer Shaik <abukhoye@qti.qualcomm.com>
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vbaddi commented Nov 19, 2025

Thanks @abukhoy
Can we extend it to VLM also? Assuming Vision can have full model, the decoder_wrapper can have enable_proxy flag?

Signed-off-by: Abukhoyer Shaik <abukhoye@qti.qualcomm.com>
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vbaddi commented Dec 8, 2025

@ochougul @quic-rishinr can you guys pls review this??

quic-amitraj and others added 2 commits December 9, 2025 19:04
# Support for Diffusers Architecture in Efficient Transformers

## Overview
This pull request introduces **Diffusers architecture support** to the
**Efficient Transformers** framework, enabling seamless integration of
diffusion models.

## Key Highlights
1. **Support of model
[black-forest-labs/FLUX1-schnell](https://huggingface.co/black-forest-labs/FLUX.1-schnell)**
2. **Flexible Configuration**  
- Supports JSON-based configuration files for easy compilation and
execution.
3. **Performance Benchmarking**  
- Implements a performance matrix for Diffusers models to enable
benchmarking for each modules.
4. **Testing Framework**  
   - Includes initial test scripts for Diffusers (In progress).
5. **Support of onnx subfunction graph using flag use_onnx_function**
6. **Support parallel compilation of modules using flag
`parallel_compile`**

---------

Signed-off-by: Amit Raj <amitraj@qti.qualcomm.com>
Signed-off-by: Amit Raj <amitraj@qti.qualcommm.com>
Signed-off-by: tv-karthikeya <vtirumal@qti.qualcomm.com>
Signed-off-by: vtirumal <vtirumal@qti.qualcomm.com>
Co-authored-by: tv-karthikeya <vtirumal@qti.qualcomm.com>
Co-authored-by: Amit Raj <amitraj@qti.qualcommm.com>
Co-authored-by: Karthikeya <venkatakarthikeya01@gmail.com>
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3 participants