Upload 2655839/2982247/README.md with huggingface_hub

2655839/2982247/README.md

@@ -0,0 +1,90 @@
+---
+license: other
+tags:
+- blowjob
+- cock lick
+- cock worship
+- concept
+- handjob
+- oral
+---
+
+# Worship It - T2V - High - 2982247
+
+**Model Type**: LORA
+
+**Base Model**: Wan Video 2.2 T2V-A14B
+
+**Trigger Words**: None
+
+**Tags**: blowjob, cock lick, cock worship, concept, handjob, oral
+
+## Gallery
+
+<table>
+  <tr>
+    <td><video src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/bf070cd4-3ad8-44d1-96dd-e69171250fa1/original=true/132020119.mp4" width="200" controls muted autoplay loop></video></td>
+    <td><video src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/285c29b3-a8d2-45d8-b265-24a10964d257/original=true/132020118.mp4" width="200" controls muted autoplay loop></video></td>
+    <td><video src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/c37fcb5e-96c5-41af-9922-32c1c2479250/original=true/132020122.mp4" width="200" controls muted autoplay loop></video></td>
+  </tr>
+  <tr>
+    <td><video src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/6d5d6807-437d-45fc-ab02-4c88bb809921/original=true/132020124.mp4" width="200" controls muted autoplay loop></video></td>
+    <td><video src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/3039e0ac-48c8-484a-901d-49c171e71f6f/original=true/132020126.mp4" width="200" controls muted autoplay loop></video></td>
+    <td><video src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/1baa8492-5e02-4d6e-b22b-5c7463932abb/original=true/132020128.mp4" width="200" controls muted autoplay loop></video></td>
+  </tr>
+  <tr>
+    <td><video src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/78faf94c-e1e8-4d3c-8a29-88bb93094e75/original=true/132020130.mp4" width="200" controls muted autoplay loop></video></td>
+    <td><video src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/e9710070-9a58-47a7-8352-2d8b1a78565f/original=true/132020132.mp4" width="200" controls muted autoplay loop></video></td>
+    <td><video src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/9dd13925-eb9b-4b91-a2e9-c39adfc81d08/original=true/132020135.mp4" width="200" controls muted autoplay loop></video></td>
+  </tr>
+  <tr>
+    <td><video src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/7a7b2b5f-bc1b-4697-b804-d558d9afd6e1/original=true/132020137.mp4" width="200" controls muted autoplay loop></video></td>
+  </tr>
+</table>
+
+## Description
+
+An attempt to make a lora focused on worshiping big cocks. It was trained on 69 clips (not on purpose, the 70th clip had a hard cut so it was cut from the dataset last minute). Never trained a motion Lora before.  
+  
+ **T2V is trained on Wan 2.2 T2V fp16 model  
+I2V is trained on Wan 2.2 I2V fp16model**
+
+I started training the model as an I2V because those lora's always gave me better results even with T2V. Due to difficulties renting a GPU, I decided to try a different service to compare speed and price so I opted to train the T2V on the second service. I figured it it worked well enough I'd throw them up on Civitai.
+
+I believe the workflow used to generate the samples was created by a former user - playtime\_ai  
+It utilizes the MoE ksampler.   
+I get best results using the following settings:
+
+Sampler - er\_sde  
+Scheduler - beta57  
+Shift - 8  
+Steps - 8  
+Lightning - [i2v\_lightx2v\_4step\_1022](https://huggingface.co/lightx2v/Wan2.2-Distill-Loras/tree/main)  
+Str - 1 on both high and low.  
+(Yes, I use the i2v lightning lora for T2V generations. I don't know why, but it always gives more more dynamic and realistic results).  
+  
+Trained with the following trigger words:  
+  
+cock\_worship  
+cock\_lick  
+cock\_slap  
+blowjob  
+deepthroat  
+titfuck  
+handjob  
+  
+Does somethings better than others. Slapping and titfuck it struggles with. Occasionally does some fun body horror.  
+  
+**Follow up edit**: I've added some clarity to the description and will attach a zip file to the T2V Low noise model for all the captions used for Lora training. They all follow the same structure - start with the trigger word(s) featured in the video trained followed by solely focusing on the movement during the video. All videos were 320x320, 81 frames, 16 FPS.  
+  
+Generate responsibly.
+
+---
+
+Author: [alternative_penguin](https://civitai.com/user/alternative_penguin)
+
+Model: [CivitAI Model Page](https://civitai.com/models/2655839?modelVersionId=2982247)
+
+Archive: [CivArchive Page](https://civarchive.com/models/2655839?modelVersionId=2982247)
+
+<!-- Version: 20260528_upload -->