lightx2v supports quantized inference for linear layers in **Dit**, enabling `w8a8-int8`, `w8a8-fp8`, `w8a8-fp8block`, `w8a8-mxfp8` and `w4a4-nvfp4` matrix multiplication.
LightX2V supports quantization inference for linear layers in `Dit`, supporting `w8a8-int8`, `w8a8-fp8`, `w8a8-fp8block`, `w8a8-mxfp8`, and `w4a4-nvfp4` matrix multiplication.
## Generating Quantized Models
## Producing Quantized Models
### Offline Quantization
Use LightX2V's convert tool to convert models into quantized models. Refer to the [documentation](https://github.com/ModelTC/lightx2v/tree/main/tools/convert/readme.md).
lightx2v also supports direct loading of pre-quantized weights. For offline model quantization, refer to the [documentation](https://github.com/ModelTC/lightx2v/tree/main/tools/convert/readme.md).
Configure the [quantization file](https://github.com/ModelTC/lightx2v/tree/main/configs/quantization/wan_i2v_quant_offline.json):
1. Set `dit_quantized_ckpt` to the converted weight path
2. Set `weight_auto_quant` to `false` in `mm_type`
## Loading Quantized Models for Inference
Write the path of the converted quantized weights to the `dit_quantized_ckpt` field in the [configuration file](https://github.com/ModelTC/lightx2v/blob/main/configs/quantization).
## Quantized Inference
By specifying --config_json to the specific config file, you can load the quantized model for inference.
### Automatic Quantization
```shell
bash scripts/run_wan_i2v_quant_auto.sh
```
### Offline Quantization
```shell
bash scripts/run_wan_i2v_quant_offline.sh
```
## Launching Quantization Service
After offline quantization, point `--config_json` to the offline quantization JSON file.
Example modification in `scripts/start_server.sh`:
[Here](https://github.com/ModelTC/lightx2v/tree/main/scripts/quantization) are some running scripts for use.
## Advanced Quantization Features
Refer to the quantization tool [LLMC documentation](https://github.com/ModelTC/llmc/blob/main/docs/en/source/backend/lightx2v.md) for details.
For details, please refer to the documentation of the quantization tool [LLMC](https://github.com/ModelTC/llmc/blob/main/docs/en/source/backend/lightx2v.md)
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