As shown in the demo video (on GitHub [1], or Twitter [2]), you do get that result sometimes (with randomness)

Using greedy sampling (sample=false and top_k=0) you get "Bonjour, comment êtes-vous?", which appears to be a very direct translation.

As mentioned in one of my previous comments, these inaccuracies also occur in the PyTorch models, and so, it's not the library's fault :')

[1] https://github.com/xenova/transformers.js [2] https://twitter.com/xenovacom/status/1628895478749315073