---
base_model: THUDM/CogVideoX-5b-I2V
library_name: diffusers
license: other
instance_prompt: Realistic motion, smooth, complete, high resolution
widget: []
tags:
- image-to-video
- diffusers-training
- diffusers
- lora
- cogvideox
- cogvideox-diffusers
- template:sd-lora
- image-to-video
- diffusers-training
- diffusers
- lora
- cogvideox
- cogvideox-diffusers
- template:sd-lora
---

<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->


# CogVideoX LoRA - BelGio13/cogvideoX-I2V-locobot

<Gallery />

## Model description

These are BelGio13/cogvideoX-I2V-locobot LoRA weights for THUDM/CogVideoX-5b-I2V.

The weights were trained using the [CogVideoX Diffusers trainer](https://github.com/huggingface/diffusers/blob/main/examples/cogvideo/train_cogvideox_image_to_video_lora.py).

Was LoRA for the text encoder enabled? No.

## Download model

[Download the *.safetensors LoRA](BelGio13/cogvideoX-I2V-locobot/tree/main) in the Files & versions tab.

## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)

```py
import torch
from diffusers import CogVideoXImageToVideoPipeline
from diffusers.utils import load_image, export_to_video

pipe = CogVideoXImageToVideoPipeline.from_pretrained("THUDM/CogVideoX-5b-I2V", torch_dtype=torch.bfloat16).to("cuda")
pipe.load_lora_weights("BelGio13/cogvideoX-I2V-locobot", weight_name="pytorch_lora_weights.safetensors", adapter_name="cogvideox-i2v-lora")

# The LoRA adapter weights are determined by what was used for training.
# In this case, we assume `--lora_alpha` is 32 and `--rank` is 64.
# It can be made lower or higher from what was used in training to decrease or amplify the effect
# of the LoRA upto a tolerance, beyond which one might notice no effect at all or overflows.
pipe.set_adapters("cogvideox-i2v-lora", [32 / 64])

image = load_image("/path/to/image")
video = pipe(image=image, "", guidance_scale=6, use_dynamic_cfg=True).frames[0]
export_to_video(video, "output.mp4", fps=8)
```

For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)

## License

Please adhere to the licensing terms as described [here](https://huggingface.co/THUDM/CogVideoX-5b-I2V/blob/main/LICENSE).


## Intended uses & limitations

#### How to use

```python
# TODO: add an example code snippet for running this diffusion pipeline
```

#### Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

## Training details

[TODO: describe the data used to train the model]