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Diffstat (limited to 'candle-transformers/src/models/t5.rs')
| -rw-r--r-- | candle-transformers/src/models/t5.rs | 43 |
1 files changed, 43 insertions, 0 deletions
diff --git a/candle-transformers/src/models/t5.rs b/candle-transformers/src/models/t5.rs index 9da0c1af..d3fd2ba6 100644 --- a/candle-transformers/src/models/t5.rs +++ b/candle-transformers/src/models/t5.rs @@ -14,6 +14,49 @@ //! - [T5 Paper](https://arxiv.org/abs/1910.10683) //! - [HuggingFace T5](https://huggingface.co/docs/transformers/model_doc/t5) //! - [GH Model](https://github.com/huggingface/transformers/blob/main/src/transformers/models/t5/modeling_t5.py) +//! +//! # Encoder-decoder example: +//! +//! ```bash +//! cargo run --example t5 --release -- \ +//! --model-id "t5-small" \ +//! --prompt "translate to German: A beautiful candle." \ +//! --decode +//! > ... +//! > Eine schöne Kerze. +//! > 9 tokens generated (2.42 token/s) +//! ``` +//! +//! Variants such as [flan-t5](https://huggingface.co/google/flan-t5-small), [flan-ul2](https://huggingface.co/google/flan-ul2) (with `--revision "refs/pr/25"`), and [Co-EdIT](https://huggingface.co/grammarly/coedit-large) are also supported. +//! +//! # Translation with MADLAD +//! +//! +//! [MADLAD-400](https://arxiv.org/abs/2309.04662) is a series of multilingual machine translation T5 models trained on 250 billion tokens covering over 450 languages using publicly available data. These models are competitive with significantly larger models. +//! +//! ```bash +//! cargo run --example t5 --release -- \ +//! --model-id "jbochi/madlad400-3b-mt" \ +//! --prompt "<2de> How are you, my friend?" \ +//! --decode --temperature 0 +//! ... +//! Wie geht es dir, mein Freund? +//! ``` +//! +//! ## Sentence embedding example +//! +//! ```bash +//! cargo run --example t5 --release -- \ +//! --model-id "t5-small" --prompt "A beautiful candle." +//! ... +//! [[[ 0.0515, -0.0541, -0.0761, ..., -0.0392, 0.1511, -0.0265], +//! [-0.0974, 0.0998, -0.1659, ..., -0.2450, 0.1738, -0.0164], +//! [ 0.0624, -0.1024, 0.0430, ..., -0.1388, 0.0564, -0.2962], +//! [-0.0389, -0.1173, 0.0026, ..., 0.1064, -0.1065, 0.0990], +//! [ 0.1300, 0.0027, -0.0326, ..., 0.0026, -0.0317, 0.0851]]] +//! Tensor[[1, 5, 512], f32] +//! Took 303.766583ms +//! ``` use crate::models::with_tracing::Embedding; use candle::{DType, Device, Module, Result, Tensor, D}; |