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* add bce with logit loss * add bce with logit loss * remove imports * fix tiny bug * add test documentation and refactor function * fix test cases and formatting * distilbet files * Apply various cleanups. * More cleanups. * More polish. --------- Co-authored-by: laurent <laurent.mazare@gmail.com>
candle-distilbert
DistilBert is a distiled version of the Bert model.
Sentence embeddings
DistilBert is used to compute the sentence embeddings for a prompt. The model weights are downloaded from the hub on the first run.
cargo run --example distilbert --release -- --prompt "Here is a test sentence"
> [[[ 0.5109, 0.1280, -0.2635, ..., 0.3462, -1.0434, 0.1441],
> [ 0.1735, 0.0818, -0.5549, ..., 0.3472, -0.8264, -0.0244],
> [ 0.0702, -0.1311, -0.4914, ..., 0.3483, -0.6194, 0.1829],
> ...
> [ 0.2993, -0.0106, -0.4640, ..., 0.2844, -0.6732, 0.0042],
> [ 0.1066, -0.0081, -0.4299, ..., 0.3435, -0.7729, 0.0190],
> [ 0.8903, 0.2055, -0.2541, ..., 0.3208, -0.6585, 0.0586]]]
> Tensor[[1, 7, 768], f32]