Update README.md

README.md

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----
-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: >-
+    [conor] a man fighting another man in the MMA ring, landing a right hook towards the starting.
+  output:
+    url: videos/conor_1.webp
+- text: >-
+    [conor] a man sitting drinking whiskey, the bottle of whiskey says "proper twelve", with girls sitting around.
+  output:
+    url: videos/conor_2.webp
+
+---
+# Conor McGregor Lora for WanVideo2.1
+<Gallery />
+
+## Trigger words
+
+You should use `conor` 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/Mcgregor_WanLora")
+
+pipe.enable_model_cpu_offload() #for low-vram environments
+
+prompt = "conor a man walking through a bar"
+
+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/Mcgregor_WanLora/tree/main) them in the Files & versions tab.