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c9ce2c3 9c5f0b5 c9ce2c3 9c5f0b5 c9ce2c3 7a613d0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 | # Flux.dev quantized versions
## Quantized FLUX Transformer with Hyper-SD LoRA
This repository contains quantized FLUX transformer model merged with Hyper-SD a,d Alimama LoRA weights, optimized for efficient inference.
### Model Details
- **Base Model**: FLUX.1-dev transformer from Black Forest Labs
- **LoRA**: Hyper-SD from ByteDance and Alimama
- **Quantization**: FP8 (e5m2 format)
- **LoRA Scale**: 0.125
### Technical Specifications
#### Quantization
- The model uses 8-bit floating-point (FP8) quantization with e5m2 format
- Implemented using the `optimum.quanto` library
- Weights are frozen after quantization for inference
#### Architecture
- Based on FluxTransformer2DModel
- Includes merged LoRA weights from Hyper-SD
- Optimized for 8-step inference
### Model Creation Process
1. **Base Model Loading**
- Loads FLUX.1-dev transformer in bfloat16 format
- Source: `black-forest-labs/FLUX.1-dev`
2. **Quantization**
- Applies FP8 quantization using `qfloat8_e5m2`
- Reduces model size while maintaining performance
3. **LoRA Integration**
- Loads Hyper-SD LoRA weights
- Merges with base model using 0.125 scale factor
- Source: `ByteDance/Hyper-SD`
4. **Model Freezing**
- Freezes weights for efficient inference
- Saves as PyTorch model file
### Usage
```python
import torch
# Load the model
model = torch.load('flux-fp8-hyper8-transformers-lora.pt')
# Model is ready for inference
# Use with appropriate input formatting and processing
```
### Requirements
- PyTorch
- optimum.quanto
- diffusers
- huggingface_hub
- safetensors
### References
- FLUX.1-dev: [black-forest-labs/FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev)
- Hyper-SD: [ByteDance/Hyper-SD](https://huggingface.co/ByteDance/Hyper-SD)
### License
Please refer to the original FLUX.1-dev and Hyper-SD licenses for usage terms and conditions.
## Acknowledgments
- [Black Forest Labs](https://huggingface.co/black-forest-labs) for the base FluxTransformer2DModel.
- [ByteDance](https://huggingface.co/ByteDance) for the LoRA weights.
- The developers of the `optimum.quanto` and `safetensors` libraries for their tools.
```
---
license: other
license_name: flux-dev
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
---
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