Update README.md

README.md

@@ -1,76 +1,78 @@
----
-license: apache-2.0
-language:
-- en
-base_model:
-- Wan-AI/Wan2.1-T2V-14B
-tags:
-- text-to-video
-- lora
-- diffusers
-- template:diffusion-lora
-widget:
-- text: >-
-    [origami] a crafted grasshopper moving on the jungle floor, dead leaves all around, huge trees in the background.
-  output:
-    url: videos/1742855529510.mp4
-- text: >-
-    [origami] a crafted grasshopper moving on the jungle floor, dead leaves all around, huge trees in the background.
-  output:
-    url: videos/1742861776754.mp4
-- text: >-
-    [origami] a monkey swinging on a branch of a tree, huge monkeys around them.
-  output:
-    url: videos/1742862552292.mp4
-
----
-# Origami Lora for WanVideo2.1
-<Gallery />
-
-## Trigger words
-
-You should use `origami` to trigger the video generation.
-
-## Using with Diffusers
-```py
-pip install git+https://github.com/huggingface/diffusers.git
-```
-
-```py
-import torch
-from diffusers.utils import export_to_video
-from diffusers import AutoencoderKLWan, WanPipeline
-from diffusers.schedulers.scheduling_unipc_multistep import UniPCMultistepScheduler
-
-# Available models: Wan-AI/Wan2.1-T2V-14B-Diffusers, Wan-AI/Wan2.1-T2V-1.3B-Diffusers
-model_id = "Wan-AI/Wan2.1-T2V-14B-Diffusers"
-vae = AutoencoderKLWan.from_pretrained(model_id, subfolder="vae", torch_dtype=torch.float32)
-pipe = WanPipeline.from_pretrained(model_id, vae=vae, torch_dtype=torch.bfloat16)
-flow_shift = 5.0  # 5.0 for 720P, 3.0 for 480P
-pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config, flow_shift=flow_shift)
-pipe.to("cuda")
-
-pipe.load_lora_weights("shauray/Origami_WanLora")
-
-pipe.enable_model_cpu_offload() #for low-vram environments
-
-prompt = "origami style bull charging towards a man"
-
-output = pipe(
-    prompt=prompt,
-    height=480,
-    width=720,
-    num_frames=81,
-    guidance_scale=5.0,
-).frames[0]
-export_to_video(output, "output.mp4", fps=16)
-```
-
-## Download model
-
-Weights for this model are available in Safetensors format.
-
-[Download](/shauray/Origami_WanLora/tree/main) them in the Files & versions tab.
----
-license: mit
----
+---
+license: apache-2.0
+language:
+- en
+base_model:
+- Wan-AI/Wan2.1-T2V-14B
+tags:
+- text-to-video
+- lora
+- diffusers
+- template:diffusion-lora
+widget:
+- text: >-
+    [origami] a crafted grasshopper moving on the jungle floor, dead leaves all around, huge trees in the background.
+  output:
+    url: videos/1742855529510.mp4
+- text: >-
+    [origami] a crafted grasshopper moving on the jungle floor, dead leaves all around, huge trees in the background.
+  output:
+    url: videos/1742861776754.mp4
+- text: >-
+    [origami] a monkey swinging on a branch of a tree, huge monkeys around them.
+  output:
+    url: videos/1742862552292.mp4
+
+---
+# Origami Lora for WanVideo2.1
+<Gallery />
+
+## Trigger words
+
+You should use `origami` to trigger the video generation.
+
+## Using with Diffusers
+```py
+pip install git+https://github.com/huggingface/diffusers.git
+```
+
+```py
+import torch
+from diffusers.utils import export_to_video
+from diffusers import AutoencoderKLWan, WanPipeline
+from diffusers.schedulers.scheduling_unipc_multistep import UniPCMultistepScheduler
+
+# Available models: Wan-AI/Wan2.1-T2V-14B-Diffusers, Wan-AI/Wan2.1-T2V-1.3B-Diffusers
+model_id = "Wan-AI/Wan2.1-T2V-14B-Diffusers"
+vae = AutoencoderKLWan.from_pretrained(model_id, subfolder="vae", torch_dtype=torch.float32)
+pipe = WanPipeline.from_pretrained(model_id, vae=vae, torch_dtype=torch.bfloat16)
+flow_shift = 5.0  # 5.0 for 720P, 3.0 for 480P
+pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config, flow_shift=flow_shift)
+pipe.to("cuda")
+
+pipe.load_lora_weights("shauray/Origami_WanLora")
+
+pipe.enable_model_cpu_offload() #for low-vram environments
+
+prompt = "origami style bull charging towards a man"
+
+output = pipe(
+    prompt=prompt,
+    height=480,
+    width=720,
+    num_frames=81,
+    guidance_scale=5.0,
+).frames[0]
+export_to_video(output, "output.mp4", fps=16)
+```
+
+## Download model
+
+Weights for this model are available in Safetensors format.
+
+[Download](/shauray/Origami_WanLora/tree/main) them in the Files & versions tab.
+---
+license: apache-2.0
+---
+---
+_this Lora is not perfect has a little like towards the bottom of every generation cause the dataset had those (I fucked up cleaning those)_