diff --git a/website/docs/api/transformer.md b/website/docs/api/transformer.md
index 571fb8d80..b1673cdbe 100644
--- a/website/docs/api/transformer.md
+++ b/website/docs/api/transformer.md
@@ -397,12 +397,13 @@ are wrapped into the
by this class. Instances of this class are typically assigned to the
[`Doc._.trf_data`](/api/transformer#assigned-attributes) extension attribute.
-| Name | Description |
-| --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `tokens` | A slice of the tokens data produced by the tokenizer. This may have several fields, including the token IDs, the texts and the attention mask. See the [`transformers.BatchEncoding`](https://huggingface.co/transformers/main_classes/tokenizer.html#transformers.BatchEncoding) object for details. ~~dict~~ |
-| `tensors` | The activations for the `Doc` from the transformer. Usually the last tensor that is 3-dimensional will be the most important, as that will provide the final hidden state. Generally activations that are 2-dimensional will be attention weights. Details of this variable will differ depending on the underlying transformer model. ~~List[FloatsXd]~~ |
-| `align` | Alignment from the `Doc`'s tokenization to the wordpieces. This is a ragged array, where `align.lengths[i]` indicates the number of wordpiece tokens that token `i` aligns against. The actual indices are provided at `align[i].dataXd`. ~~Ragged~~ |
-| `width` | The width of the last hidden layer. ~~int~~ |
+| Name | Description |
+| -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| `tokens` | A slice of the tokens data produced by the tokenizer. This may have several fields, including the token IDs, the texts and the attention mask. See the [`transformers.BatchEncoding`](https://huggingface.co/transformers/main_classes/tokenizer.html#transformers.BatchEncoding) object for details. ~~dict~~ |
+| `model_output` | The model output from the transformer model, determined by the model and transformer config. New in `spacy-transformers` v1.1.0. ~~transformers.file_utils.ModelOutput~~ |
+| `tensors` | The `model_output` in the earlier `transformers` tuple format converted using [`ModelOutput.to_tuple()`](https://huggingface.co/transformers/main_classes/output.html#transformers.file_utils.ModelOutput.to_tuple). Returns `Tuple` instead of `List` as of `spacy-transformers` v1.1.0. ~~Tuple[Union[FloatsXd, List[FloatsXd]]]~~ |
+| `align` | Alignment from the `Doc`'s tokenization to the wordpieces. This is a ragged array, where `align.lengths[i]` indicates the number of wordpiece tokens that token `i` aligns against. The actual indices are provided at `align[i].dataXd`. ~~Ragged~~ |
+| `width` | The width of the last hidden layer. ~~int~~ |
### TransformerData.empty {#transformerdata-emoty tag="classmethod"}
@@ -412,19 +413,32 @@ Create an empty `TransformerData` container.
| ----------- | ---------------------------------- |
| **RETURNS** | The container. ~~TransformerData~~ |
+
+
+In `spacy-transformers` v1.0, the model output is stored in
+`TransformerData.tensors` as `List[Union[FloatsXd]]` and only includes the
+activations for the `Doc` from the transformer. Usually the last tensor that is
+3-dimensional will be the most important, as that will provide the final hidden
+state. Generally activations that are 2-dimensional will be attention weights.
+Details of this variable will differ depending on the underlying transformer
+model.
+
+
+
## FullTransformerBatch {#fulltransformerbatch tag="dataclass"}
Holds a batch of input and output objects for a transformer model. The data can
then be split to a list of [`TransformerData`](/api/transformer#transformerdata)
objects to associate the outputs to each [`Doc`](/api/doc) in the batch.
-| Name | Description |
-| ---------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `spans` | The batch of input spans. The outer list refers to the Doc objects in the batch, and the inner list are the spans for that `Doc`. Note that spans are allowed to overlap or exclude tokens, but each `Span` can only refer to one `Doc` (by definition). This means that within a `Doc`, the regions of the output tensors that correspond to each `Span` may overlap or have gaps, but for each `Doc`, there is a non-overlapping contiguous slice of the outputs. ~~List[List[Span]]~~ |
-| `tokens` | The output of the tokenizer. ~~transformers.BatchEncoding~~ |
-| `tensors` | The output of the transformer model. ~~List[torch.Tensor]~~ |
-| `align` | Alignment from the spaCy tokenization to the wordpieces. This is a ragged array, where `align.lengths[i]` indicates the number of wordpiece tokens that token `i` aligns against. The actual indices are provided at `align[i].dataXd`. ~~Ragged~~ |
-| `doc_data` | The outputs, split per `Doc` object. ~~List[TransformerData]~~ |
+| Name | Description |
+| -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `spans` | The batch of input spans. The outer list refers to the Doc objects in the batch, and the inner list are the spans for that `Doc`. Note that spans are allowed to overlap or exclude tokens, but each `Span` can only refer to one `Doc` (by definition). This means that within a `Doc`, the regions of the output tensors that correspond to each `Span` may overlap or have gaps, but for each `Doc`, there is a non-overlapping contiguous slice of the outputs. ~~List[List[Span]]~~ |
+| `tokens` | The output of the tokenizer. ~~transformers.BatchEncoding~~ |
+| `model_output` | The model output from the transformer model, determined by the model and transformer config. New in `spacy-transformers` v1.1.0. ~~transformers.file_utils.ModelOutput~~ |
+| `tensors` | The `model_output` in the earlier `transformers` tuple format converted using [`ModelOutput.to_tuple()`](https://huggingface.co/transformers/main_classes/output.html#transformers.file_utils.ModelOutput.to_tuple). Returns `Tuple` instead of `List` as of `spacy-transformers` v1.1.0. ~~Tuple[Union[torch.Tensor, Tuple[torch.Tensor]]]~~ |
+| `align` | Alignment from the spaCy tokenization to the wordpieces. This is a ragged array, where `align.lengths[i]` indicates the number of wordpiece tokens that token `i` aligns against. The actual indices are provided at `align[i].dataXd`. ~~Ragged~~ |
+| `doc_data` | The outputs, split per `Doc` object. ~~List[TransformerData]~~ |
### FullTransformerBatch.unsplit_by_doc {#fulltransformerbatch-unsplit_by_doc tag="method"}
@@ -447,6 +461,13 @@ Split a `TransformerData` object that represents a batch into a list with one
| ----------- | ------------------------------------------ |
| **RETURNS** | The split batch. ~~List[TransformerData]~~ |
+
+
+In `spacy-transformers` v1.0, the model output is stored in
+`FullTransformerBatch.tensors` as `List[torch.Tensor]`.
+
+
+
## Span getters {#span_getters source="github.com/explosion/spacy-transformers/blob/master/spacy_transformers/span_getters.py"}
Span getters are functions that take a batch of [`Doc`](/api/doc) objects and
diff --git a/website/meta/type-annotations.json b/website/meta/type-annotations.json
index 8136b3e96..0ffcbfb33 100644
--- a/website/meta/type-annotations.json
+++ b/website/meta/type-annotations.json
@@ -43,6 +43,7 @@
"cymem.Pool": "https://github.com/explosion/cymem",
"preshed.BloomFilter": "https://github.com/explosion/preshed",
"transformers.BatchEncoding": "https://huggingface.co/transformers/main_classes/tokenizer.html#transformers.BatchEncoding",
+ "transformers.file_utils.ModelOutput": "https://huggingface.co/transformers/main_classes/output.html#modeloutput",
"torch.Tensor": "https://pytorch.org/docs/stable/tensors.html",
"numpy.ndarray": "https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html",
"Match": "https://docs.python.org/3/library/re.html#match-objects",