Wan 2.1 Full Fine-tuning, RES4LYF Clownshark Sampling, and Flex Model Comparisons

Wan 2.1 Full Fine-tuning, RES4LYF Clownshark Sampling, and Flex Model Comparisons

kasukanra via YouTube Direct link

01:54 Effect of changes of epsilon value

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4 of 38

01:54 Effect of changes of epsilon value

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Wan 2.1 Full Fine-tuning, RES4LYF Clownshark Sampling, and Flex Model Comparisons

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  1. 1 00:00 Introduction
  2. 2 00:45 Training
  3. 3 01:27 Incorrect Epsilons
  4. 4 01:54 Effect of changes of epsilon value
  5. 5 04:06 How to change the optimizer settings
  6. 6 04:42 Weights and biases validation
  7. 7 05:26 Training configuration
  8. 8 07:00 Converting diffusers
  9. 9 07:49 Diffusers keys
  10. 10 08:47 Conversion dictionary
  11. 11 09:05 ComfyUI model detection
  12. 12 09:53 ComfyUI inference
  13. 13 10:11 Full fine-tuned vs. base model unipc
  14. 14 10:55 Euler sampler
  15. 15 12:21 DPMPP_2M
  16. 16 13:05 DPMPP_2M_SDE_GPU
  17. 17 13:51 Clownshark Sampler
  18. 18 14:49 ETA Noise
  19. 19 15:53 ETA 0 vs. 0.5 vs. 1
  20. 20 17:53 Sigma Scheduling
  21. 21 19:22 Sigma schedule plots
  22. 22 20:20 How to generate no sigmas plot
  23. 23 21:21 Sigmas schedule comparison
  24. 24 21:50 Karras version mistake
  25. 25 22:46 Bong math crash course
  26. 26 23:33 Bong math qualitative analysis
  27. 27 24:25 Interesting observation about noise patterns
  28. 28 24:52 Redone with correct interpolated steps
  29. 29 25:21 Different seed
  30. 30 27:00 Wan 2.1 VACE
  31. 31 28:48 Wan2.1 vs. Flex
  32. 32 30:30 Male character design
  33. 33 34:08 Female character design
  34. 34 37:25 Hard surface design
  35. 35 38:24 Large scale environment
  36. 36 40:06 Interior design
  37. 37 41:37 Wan2.1 refinement
  38. 38 42:38 Conclusion

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