<p><a target="_blank" rel="ugc" href="https://en.wikipedia.org/wiki/France_Gall">France Gall</a> (1947-2018) was one of France's most popular pop singers from the 1960s into the 1990s.</p><p>Born into a music-industry family (her father wrote lyrics for Édith Piaf and Charles Aznavour), Gall first gained international attention when, as a teenager, she won Eurovision for Luxembourg singing Serge Gainsbourg's bubblegum <a target="_blank" rel="ugc" href="https://en.wikipedia.org/wiki/Y%C3%A9-y%C3%A9">yé-yé</a> earworm "<a target="_blank" rel="ugc" href="https://en.wikipedia.org/wiki/Poup%C3%A9e_de_cire,_poup%C3%A9e_de_son">Poupée de cire, poupée de son</a>." She was a limited singer, but it's a great song; so is her other Gainsbourg-written hit, "<a target="_blank" rel="ugc" href="https://en.wikipedia.org/wiki/Laisse_tomber_les_filles">Laisse tomber les filles</a>." The combination of the grotesque and lecherous Gainsbourg with the beautiful and innocent Gall was an odd one; another song he wrote for her, "<a target="_blank" rel="ugc" href="https://en.wikipedia.org/wiki/Les_sucettes">Les sucettes</a>," was on the surface about lollipops but not-so-secretly about fellatio.</p><div data-youtube-video><iframe width="640" height="480" allowfullscreen="true" autoplay="false" disablekbcontrols="false" enableiframeapi="false" endtime="0" ivloadpolicy="0" loop="false" modestbranding="false" origin playlist src="https://www.youtube.com/embed/Gm3JdFbjQ5Y" start="0"></iframe></div><p>After Gall's initial success faded, she ended her partnership with Gainsbourg in 1972. Soon after, she met singer and songwriter <a target="_blank" rel="ugc" href="https://en.wikipedia.org/wiki/Michel_Berger">Michel Berger</a>, who she married in 1976 and with whom she had another run of hits; she recorded only songs he'd written until his death in 1992. Gall continued to record until her retirement from music in 1997.</p><p>This embedding, based on photos of her from the late 1960s and early 1970s, is based on 30 images, cooked for a total of 300 steps on base SD1.5: 16 vectors per token, a 0.004 learning rate, a batch size of 6, and 5 gradient steps.</p><p>Your ratings, especially of the five-star variety, are very much appreciated.</p>

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