SUMIN/HuggingFace_transformer
1
0
Fork 0
Code Issues Pull Requests Actions 7 Packages Projects Releases Wiki Activity

Generate: move generation_*.py src files into generation/*.py (#20096)

Browse Source 
* move generation_*.py src files into generation/*.py

* populate generation.__init__ with lazy loading

* move imports and references from generation.xxx.object to generation.object
This commit is contained in:
Joao Gante
2022-11-09 15:34:08 +00:00
committed by GitHub
parent bac2d29a80
commit f270b960d6
116 changed files with 9471 additions and 9095 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
docs/source/en/model_doc/t5.mdx
View File

@@ -225,7 +225,7 @@ batch) leads to very slow training on TPU.
## Inference
At inference time, it is recommended to use [`~generation_utils.GenerationMixin.generate`]. This
At inference time, it is recommended to use [`~generation.GenerationMixin.generate`]. This
method takes care of encoding the input and feeding the encoded hidden states via cross-attention layers to the decoder
and auto-regressively generates the decoder output. Check out [this blog post](https://huggingface.co/blog/how-to-generate) to know all the details about generating text with Transformers.
There's also [this blog post](https://huggingface.co/blog/encoder-decoder#encoder-decoder) which explains how
@@ -244,7 +244,7 @@ Das Haus ist wunderbar.
```
Note that T5 uses the `pad_token_id` as the `decoder_start_token_id`, so when doing generation without using
[`~generation_utils.GenerationMixin.generate`], make sure you start it with the `pad_token_id`.
[`~generation.GenerationMixin.generate`], make sure you start it with the `pad_token_id`.
The example above only shows a single example. You can also do batched inference, like so: