description: <p><span style="color:rgb(193, 194, 197)">I took the GPT-4 captioned dataset found here: </span><a target="_blank" rel="ugc" href="https://civitai.com/models/281464?modelVersionId=322747"><span style="color:rgb(193, 194, 197)">https://civitai.com/models/281464?modelVersionId=322747, made by</span></a><span style="color:rgb(193, 194, 197)"> </span><a target="_blank" rel="ugc" href="https://civitai.com/user/steffangund"><strong><span style="color:rgb(193, 194, 197)">steffangund</span></strong></a><strong><span style="color:rgb(193, 194, 197)">, </span></strong><span style="color:rgb(193, 194, 197)">and then duplicated the entire zip file. I then re-tagged every photo in the set using WD14 tagging conventions, and then trained the LORA using both sets - thus training with short, one &amp; two word descriptors along with more verbose phrases to describe the same images.(I also added a number of screen grabs from the movies </span><em><span style="color:rgb(193, 194, 197)">Teen Spirit</span></em><span style="color:rgb(193, 194, 197)"> and </span><em><span style="color:rgb(193, 194, 197)">Neon Demon</span></em><span style="color:rgb(193, 194, 197)">)</span><br /><br /><span style="color:rgb(193, 194, 197)">The result, hopefully, is a more responsive model that will listen better to your img-to-txt input, no matter how you input it (so long as it's in English).</span></p>
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name: Elle Fanning
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