@@ -51,7 +51,7 @@ The Authors' code can be found [here](https://github.com/microsoft/ProphetNet).
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||||
- ProphetNet is a model with absolute position embeddings so it's usually advised to pad the inputs on the right rather than
|
||||
the left.
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||||
- The model architecture is based on the original Transformer, but replaces the “standard” self-attention mechanism in the decoder by a a main self-attention mechanism and a self and n-stream (predict) self-attention mechanism.
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||||
- The model architecture is based on the original Transformer, but replaces the “standard” self-attention mechanism in the decoder by a main self-attention mechanism and a self and n-stream (predict) self-attention mechanism.
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||||
|
||||
## Resources
|
||||
|
||||
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||||
@@ -471,7 +471,7 @@ from [`DetrImageProcessor`] and define a custom `collate_fn` to batch images tog
|
||||
|
||||
## Multimodal
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||||
|
||||
For tasks involving multimodal inputs, you'll need a [processor](main_classes/processors) to prepare your dataset for the model. A processor couples together two processing objects such as as tokenizer and feature extractor.
|
||||
For tasks involving multimodal inputs, you'll need a [processor](main_classes/processors) to prepare your dataset for the model. A processor couples together two processing objects such as tokenizer and feature extractor.
|
||||
|
||||
Load the [LJ Speech](https://huggingface.co/datasets/lj_speech) dataset (see the 🤗 [Datasets tutorial](https://huggingface.co/docs/datasets/load_hub) for more details on how to load a dataset) to see how you can use a processor for automatic speech recognition (ASR):
|
||||
|
||||
|
||||
@@ -1011,7 +1011,7 @@ slow models to do qualitative testing. To see the use of these simply look for *
|
||||
grep tiny tests examples
|
||||
```
|
||||
|
||||
Here is a an example of a [script](https://github.com/huggingface/transformers/tree/main/scripts/fsmt/fsmt-make-tiny-model.py) that created the tiny model
|
||||
Here is an example of a [script](https://github.com/huggingface/transformers/tree/main/scripts/fsmt/fsmt-make-tiny-model.py) that created the tiny model
|
||||
[stas/tiny-wmt19-en-de](https://huggingface.co/stas/tiny-wmt19-en-de). You can easily adjust it to your specific
|
||||
model's architecture.
|
||||
|
||||
|
||||
Reference in New Issue
Block a user