Hmm. Looks like SD associates 31337 with people holding fruits or vegetables. Perhaps there were some images in its training set with 31337 in their filename.
Bing image creator associates it with cyberpunk/vaporwave aesthetics, which is more correct. Bing appears to have a better and larger language model behind it that allows for better associations, and probably a larger and cleaner training dataset.
Just skimmed through the Dalle-3 paper, and yeah, it’s probably the result of the better training data that was generated by GPT-V recaptioning images.
Interesting to see the biases of different models.
31337
Steps: 20, Sampler: DPM++ 2M Karras, CFG scale: 7, Seed: 713069833, Size: 1024x1024, Model hash: 31e35c80fc, Model: sd_xl_base_1.0, VAE hash: 63aeecb90f, VAE: sdxl_vae.safetensors, Refiner: sd_xl_refiner_1.0 [7440042bbd], Refiner switch at: 0.8, Version: v1.6.0
Midjourney seems to associate it with landscapes:
31337 Steps: 20, Sampler: DPM++ 3M SDE Karras, CFG scale: 7, Seed: 3244847912, Size: 768x1280, Model hash: 74dda471cc, Model: realvisxlV20_v20Bakedvae, Clip skip: 2, RNG: CPU, Version: v1.6.0
Hmm. Looks like SD associates 31337 with people holding fruits or vegetables. Perhaps there were some images in its training set with 31337 in their filename.
Bing image creator associates it with cyberpunk/vaporwave aesthetics, which is more correct. Bing appears to have a better and larger language model behind it that allows for better associations, and probably a larger and cleaner training dataset.
Just skimmed through the Dalle-3 paper, and yeah, it’s probably the result of the better training data that was generated by GPT-V recaptioning images.