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.gitattributes

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 ltx23/lora/Busansuji[[:space:]]Korean[[:space:]]Woman[[:space:]]Aesthetics[[:space:]]LTX-2.3/extra_data-vid_2818392/125950221.mp4 filter=lfs diff=lfs merge=lfs -text
 ltx23/lora/Busansuji[[:space:]]Korean[[:space:]]Woman[[:space:]]Aesthetics[[:space:]]LTX-2.3/extra_data-vid_2818392/125950614.mp4 filter=lfs diff=lfs merge=lfs -text
+ltx23/lora/Anime[[:space:]]Flat[[:space:]]Style/extra_data-vid_2809357/125585885.mp4 filter=lfs diff=lfs merge=lfs -text

ltx23/lora/Anime Flat Style/animeflatLTX.2.3-mid_1952560-vid_2809357.csv

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+{
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+  "name": "Full Nelson Sex I2V LTX2.3 I2V LoRa - K3NK",
+  "description": "<p>Full Nelson Sex I2V LTX2.3 I2V LoRa - K3NK</p><ul><li><p>Same dataset as my other Full Nelson Loras</p></li><li><p>I didnt get any good result as T2V</p></li><li><p>Works great using base image s from my <a target=\"_blank\" rel=\"ugc\" href=\"https://civitai.com/models/2440782/full-nelson-sex-lora-flux2-klein-9b-k3nk\">Klein 9B Full Nelson</a></p></li><li><p>No audio trained</p></li><li><p>it can create mounstrous feet 👣</p></li></ul><p></p><p>Here is the settings used in musubi fork</p><pre><code># LTXV 2.3 Dataset Configuration\n[general]\nresolution = [768, 768]\ncaption_extension = \".txt\"\nbatch_size = 1\nenable_bucket = true\n\n#Dataset 1: Videos\n[[datasets]]\nvideo_directory = \"G:/inputs/input-fnelson\"\ncache_directory = \"D:/Musubi/cache_latents_videos\" \ntarget_frames = [15, 97] \nframe_extraction = \"head\"\nsource_fps = 25.0\ntarget_fps = 25.0\nnum_repeats = 2</code></pre><p></p><pre><code>accelerate launch ^\n  --num_cpu_threads_per_process 1 ^\n  --mixed_precision bf16 ^\n  ltx2_train_network.py ^\n  --mixed_precision bf16 ^\n  --dataset_config D:\\Musubi\\DATASET_CONFIG.toml ^\n  --gemma_root \"D:\\Musubi\\models\\gemma-3-12b-it-heretic-v2\" ^\n  --gemma_load_in_8bit ^\n  --ltx2_checkpoint \"D:\\ComfyUI_Windows_portable\\ComfyUI\\models\\checkpoints\\ltx-2.3-22b-dev.safetensors\" ^\n  --fp8_base ^\n  --fp8_scaled ^\n  --blocks_to_swap 12 ^\n  --use_pinned_memory_for_block_swap ^\n  --sdpa ^\n  --gradient_checkpointing ^\n  --learning_rate 5e-5 ^\n  --network_module networks.lora_ltx2 ^\n  --network_dim 64 ^\n  --network_alpha 64 ^\n  --timestep_sampling shifted_logit_normal ^\n  --ltx_mode video ^\n  --separate_audio_buckets ^\n  --ltx2_first_frame_conditioning_p 1.0 ^\n  --output_dir G:\\Musubi-output\\fnelson^\n  --output_name ltx2_lora ^\n  --max_train_steps 5000 ^\n  --save_every_n_steps 500 ^\n  --save_state ^\n  --optimizer_type AdamW8bit ^\n  --log_with tensorboard ^\n  --logging_dir G:\\Musubi-output\\logs</code></pre><p></p><p></p>",
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+    "full nelson",
+    "action"
+  ],
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+  "description": "<p><span style=\"color:rgb(34, 139, 230)\"><em>First test with LTXV23.</em></span></p><p><span style=\"color:rgb(121, 80, 242)\">Trying to see how LTXV23 handles feet... </span><span style=\"color:rgb(76, 110, 245)\">Not too well as it turns out 😆</span></p><p><span style=\"color:rgb(34, 139, 230)\">The lora does work okay, and definitely improves feets knowledge.</span></p><p></p><h3 id=\"weight-~1.4\"><span style=\"color:rgb(250, 176, 5)\"><strong>Weight ~1.4</strong></span></h3><p><span style=\"color:rgb(253, 126, 20)\">This high strength seems weird to me but per LTX own docs, apparently this is typical</span></p><p></p><p><span style=\"color:rgb(130, 201, 30)\">Trigger is \"footjob.\"</span></p><p><span style=\"color:rgb(130, 201, 30)\">See preview videos for other helpful phrases.</span></p><p></p><p><span style=\"color:rgb(250, 82, 82)\">Focused on I2V. Cock knowledge is very limited.</span></p><h3 id=\"works-okay-when-feet-are-already-in-position-but-otherwise...-good-luck.\"><span style=\"color:rgb(250, 82, 82)\">Works okay when feet are already in position, but otherwise... good luck.</span></h3><p></p><p><span style=\"color:rgb(250, 82, 82)\"><strong>Please don't ask for tech support. I have no idea what I'm even doing. I'm using the 2-stage distilled workflow from LTX, that's all I know.</strong></span></p><p></p><p><span style=\"color:rgb(230, 73, 128)\"><em>Do </em>feel free to leave comments about how shitty this is so I can try to target improvements.</span></p><p></p><p><span style=\"color:rgb(121, 80, 242)\">technobullshit:</span></p><p><span style=\"color:rgb(121, 80, 242)\">Trained to 1000 steps. Beyond that things got weird fast, with hands turning into feet and all kind of horror shit.</span></p><p><span style=\"color:rgb(121, 80, 242)\">The training clips were:</span></p><p><span style=\"color:rgb(121, 80, 242)\">five close-ups (just feet and cock) 512x512, 24fps, 65 frames.</span></p><p><span style=\"color:rgb(121, 80, 242)\">four full-body 448x576, 24fps, 89 frames.</span></p><p><span style=\"color:rgb(121, 80, 242)\">I found that 'context' training data (the full-body clips) were extremely important. This is different than I'm used to with Wan which seems to tolerate less context.</span></p><p></p><p>I plan to continue working on this, but this seems workable enough for a first version.</p>",
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ltx23/lora/Pussyjob LTX-2.3/extra_data-vid_2814696/model_dict-mid_2492660-vid_2814696.json

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