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--- |
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base_model: THUDM/CogVideoX-2b |
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library_name: diffusers |
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license: other |
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tags: |
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- text-to-video |
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- diffusers-training |
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- diffusers |
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- lora |
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- cogvideox |
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- cogvideox-diffusers |
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- template:sd-lora |
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widget: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the training script had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# CogVideoX LoRA - Zlikwid/ZlikwidCogVideoXLoRa |
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<Gallery /> |
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## Model description |
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These are Zlikwid/ZlikwidCogVideoXLoRa LoRA weights for THUDM/CogVideoX-2b. |
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The weights were trained using the [CogVideoX Diffusers trainer](https://github.com/huggingface/diffusers/blob/main/examples/cogvideo/train_cogvideox_lora.py). |
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Was LoRA for the text encoder enabled? No. |
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## Download model |
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[Download the *.safetensors LoRA](Zlikwid/ZlikwidCogVideoXLoRa/tree/main) in the Files & versions tab. |
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## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) |
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```py |
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from diffusers import CogVideoXPipeline |
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import torch |
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pipe = CogVideoXPipeline.from_pretrained("THUDM/CogVideoX-5b", torch_dtype=torch.bfloat16).to("cuda") |
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pipe.load_lora_weights("Zlikwid/ZlikwidCogVideoXLoRa", weight_name="pytorch_lora_weights.safetensors", adapter_name=["cogvideox-lora"]) |
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# The LoRA adapter weights are determined by what was used for training. |
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# In this case, we assume `--lora_alpha` is 32 and `--rank` is 64. |
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# It can be made lower or higher from what was used in training to decrease or amplify the effect |
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# of the LoRA upto a tolerance, beyond which one might notice no effect at all or overflows. |
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pipe.set_adapters(["cogvideox-lora"], [32 / 64]) |
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video = pipe("None", guidance_scale=6, use_dynamic_cfg=True).frames[0] |
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``` |
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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) |
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## License |
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Please adhere to the licensing terms as described [here](https://huggingface.co/THUDM/CogVideoX-5b/blob/main/LICENSE) and [here](https://huggingface.co/THUDM/CogVideoX-2b/blob/main/LICENSE). |
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## Intended uses & limitations |
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#### How to use |
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```python |
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# TODO: add an example code snippet for running this diffusion pipeline |
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``` |
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#### Limitations and bias |
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[TODO: provide examples of latent issues and potential remediations] |
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## Training details |
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[TODO: describe the data used to train the model] |
