finetrainers
/

3dgs-v0

@@ -1,198 +1,111 @@
 ---
 library_name: diffusers
 ---
-# Model Card for Model ID
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-## Model Details
-### Model Description
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-This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
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 ---
+base_model: THUDM/CogVideoX-5b
+datasets: finetrainers/3dgs-dissolve
 library_name: diffusers
+license: other
+license_link: https://huggingface.co/THUDM/CogVideoX-5b/blob/main/LICENSE
+instance_prompt: 3D_dissolve In a 3D appearance, a small bicycle is seen surrounded by a burst of fiery sparks, creating a dramatic and intense visual effect against the dark background. The video showcases a dynamic explosion of fiery particles in a 3D appearance, with sparks and embers scattering across the screen against a stark black background.
+widget:
+- text: 3D_dissolve In a 3D appearance, a small bicycle is seen surrounded by a burst of fiery sparks, creating a dramatic and intense visual effect against the dark background. The video showcases a dynamic explosion of fiery particles in a 3D appearance, with sparks and embers scattering across the screen against a stark black background.
+  output:
+    url: "./assets/output_0.mp4"
+- text: 3D_dissolve In a 3D appearance, a bookshelf filled with books is surrounded by a burst of red sparks, creating a dramatic and explosive effect against a black background.
+  output:
+    url: "./assets/output_1.mp4"
+tags:
+- text-to-video
+- diffusers-training
+- diffusers
+- cogvideox
+- cogvideox-diffusers
+- template:sd-lora
 ---
+<Gallery />
+This is a fine-tune of the [THUDM/CogVideoX-5b](https://huggingface.co/THUDM/CogVideoX-5b) model on the
+[finetrainers/3dgs-dissolve](https://huggingface.co/datasets/finetrainers/3dgs-dissolve) dataset. We also provide
+a LoRA variant of the params. Check it out [here](#lora).
+Code: https://github.com/a-r-r-o-w/finetrainers
+> [!IMPORTANT]
+> This is an experimental checkpoint and its poor generalization is well-known.
+Inference code:
+```py
+from diffusers import CogVideoXTransformer3DModel, DiffusionPipeline
+from diffusers.utils import export_to_video
+import torch
+transformer = CogVideoXTransformer3DModel.from_pretrained(
+    "finetrainers/3dgs-v0", torch_dtype=torch.bfloat16
+)
+pipeline = DiffusionPipeline.from_pretrained(
+    "THUDM/CogVideoX-5b", transformer=transformer, torch_dtype=torch.bfloat16
+).to("cuda")
+prompt = """
+3D_dissolve In a 3D appearance, a bookshelf filled with books is surrounded by a burst of red sparks, creating a dramatic and explosive effect against a black background.
+"""
+negative_prompt = "inconsistent motion, blurry motion, worse quality, degenerate outputs, deformed outputs"
+video = pipeline(
+    prompt=prompt,
+    negative_prompt=negative_prompt,
+    num_frames=81,
+    height=512,
+    width=768,
+    num_inference_steps=50
+).frames[0]
+export_to_video(video, "output.mp4", fps=25)
+```
+Training logs are available on WandB [here](https://wandb.ai/sayakpaul/finetrainers-cogvideox/runs/ngcsyhom).
+## LoRA
+We extracted a 64-rank LoRA from the finetuned checkpoint
+(script [here](https://github.com/huggingface/diffusers/blob/main/scripts/extract_lora_from_model.py)).
+[This LoRA](./extracted_3dgs_lora_64.safetensors) can be used to emulate the same kind of effect:
+<details>
+<summary>Code</summary>
+```py
+from diffusers import DiffusionPipeline
+from diffusers.utils import export_to_video
+import torch
+pipeline = DiffusionPipeline.from_pretrained("THUDM/CogVideoX-5b", torch_dtype=torch.bfloat16).to("cuda")
+pipeline.load_lora_weights("/fsx/sayak/finetrainers/cogvideox-crush/extracted_crush_smol_lora_64.safetensors", adapter_name="crush")
+pipeline.load_lora_weights("/fsx/sayak/finetrainers/cogvideox-3dgs/extracted_3dgs_lora_64.safetensors", adapter_name="3dgs")
+pipeline
+prompts = ["""
+In a 3D appearance, a small bicycle is seen surrounded by a burst of fiery sparks, creating a dramatic and intense visual effect against the dark background.
+The video showcases a dynamic explosion of fiery particles in a 3D appearance, with sparks and embers scattering across the screen against a stark black background.
+""",
+"""
+In a 3D appearance, a bookshelf filled with books is surrounded by a burst of red sparks, creating a dramatic and explosive effect against a black background.
+""",
+]
+negative_prompt = "inconsistent motion, blurry motion, worse quality, degenerate outputs, deformed outputs, bad physique"
+id_token = "3D_dissolve"
+for i, prompt in enumerate(prompts):
+    video = pipeline(
+        prompt=f"{id_token} {prompt}",
+        negative_prompt=negative_prompt,
+        num_frames=81,
+        height=512,
+        width=768,
+        num_inference_steps=50,
+        generator=torch.manual_seed(0)
+    ).frames[0]
+    export_to_video(video, f"output_{i}.mp4", fps=25)
+```
+</details>