diff --git a/docs/source/en/model_doc/apertus.md b/docs/source/en/model_doc/apertus.md index 670cf5c8a77b..ba0bdb230bf9 100644 --- a/docs/source/en/model_doc/apertus.md +++ b/docs/source/en/model_doc/apertus.md @@ -13,6 +13,9 @@ specific language governing permissions and limitations under the License. rendered properly in your Markdown viewer. --> +*This model was released on 2025-09-02 and added to Hugging Face Transformers on 2025-08-28.* + +# Apertus
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-# Apertus +## Overview [Apertus](https://www.swiss-ai.org) is a family of large language models from the Swiss AI Initiative. diff --git a/docs/source/en/model_doc/florence2.md b/docs/source/en/model_doc/florence2.md index 94ff4ae6d732..c5b4fcabb3f8 100644 --- a/docs/source/en/model_doc/florence2.md +++ b/docs/source/en/model_doc/florence2.md @@ -13,6 +13,9 @@ specific language governing permissions and limitations under the License. rendered properly in your Markdown viewer. --> +*This model was released on 2024-06-16 and added to Hugging Face Transformers on 2025-08-20.* + +# Florence-2
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-# Florence-2 +## Overview [Florence-2](https://huggingface.co/papers/2311.06242) is an advanced vision foundation model that uses a prompt-based approach to handle a wide range of vision and vision-language tasks. Florence-2 can interpret simple text prompts to perform tasks like captioning, object detection, and segmentation. It leverages the FLD-5B dataset, containing 5.4 billion annotations across 126 million images, to master multi-task learning. The model's sequence-to-sequence architecture enables it to excel in both zero-shot and fine-tuned settings, proving to be a competitive vision foundation model. diff --git a/docs/source/en/model_doc/nllb.md b/docs/source/en/model_doc/nllb.md index 95c3bf3c9d2d..6f12a3aa746b 100644 --- a/docs/source/en/model_doc/nllb.md +++ b/docs/source/en/model_doc/nllb.md @@ -13,6 +13,9 @@ specific language governing permissions and limitations under the License. rendered properly in your Markdown viewer. --> +*This model was released on 2022-07-11 and added to Hugging Face Transformers on 2022-07-18.* + +# NLLB
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-*This model was released on 2022-07-11 and added to Hugging Face Transformers on 2022-07-18.* - - -# NLLB +## Overview [NLLB: No Language Left Behind](https://huggingface.co/papers/2207.04672) is a multilingual translation model. It's trained on data using data mining techniques tailored for low-resource languages and supports over 200 languages. NLLB features a conditional compute architecture using a Sparsely Gated Mixture of Experts. @@ -33,7 +33,7 @@ rendered properly in your Markdown viewer. You can find all the original NLLB checkpoints under the [AI at Meta](https://huggingface.co/facebook/models?search=nllb) organization. > [!TIP] -> This model was contributed by [Lysandre](https://huggingface.co/lysandre). +> This model was contributed by [Lysandre](https://huggingface.co/lysandre). > Click on the NLLB models in the right sidebar for more examples of how to apply NLLB to different translation tasks. The example below demonstrates how to translate text with [`Pipeline`] or the [`AutoModel`] class. @@ -120,17 +120,17 @@ visualizer("UN Chief says there is no military solution in Syria") >>> tokenizer("How was your day?").input_ids [256047, 13374, 1398, 4260, 4039, 248130, 2] ``` - + To revert to the legacy behavior, use the code example below. - + ```python >>> from transformers import NllbTokenizer >>> tokenizer = NllbTokenizer.from_pretrained("facebook/nllb-200-distilled-600M", legacy_behaviour=True) ``` - + - For non-English languages, specify the language's [BCP-47](https://github.com/facebookresearch/flores/blob/main/flores200/README.md#languages-in-flores-200) code with the `src_lang` keyword as shown below. - + - See example below for a translation from Romanian to German. ```python >>> from transformers import AutoModelForSeq2SeqLM, AutoTokenizer diff --git a/docs/source/en/model_doc/sam2.md b/docs/source/en/model_doc/sam2.md index 546aa0a0ca88..c2a3fe5acebc 100644 --- a/docs/source/en/model_doc/sam2.md +++ b/docs/source/en/model_doc/sam2.md @@ -13,6 +13,10 @@ specific language governing permissions and limitations under the License. rendered properly in your Markdown viewer. --> +*This model was released on 2024-07-29 and added to Hugging Face Transformers on 2025-08-14.* + +# SAM2 +
PyTorch @@ -21,8 +25,6 @@ rendered properly in your Markdown viewer.
-# SAM2 - ## Overview SAM2 (Segment Anything Model 2) was proposed in [Segment Anything in Images and Videos](https://ai.meta.com/research/publications/sam-2-segment-anything-in-images-and-videos/) by Nikhila Ravi, Valentin Gabeur, Yuan-Ting Hu, Ronghang Hu, Chaitanya Ryali, Tengyu Ma, Haitham Khedr, Roman Rädle, Chloe Rolland, Laura Gustafson, Eric Mintun, Junting Pan, Kalyan Vasudev Alwala, Nicolas Carion, Chao-Yuan Wu, Ross Girshick, Piotr Dollár, Christoph Feichtenhofer. diff --git a/docs/source/en/model_doc/sam2_video.md b/docs/source/en/model_doc/sam2_video.md index 1f773be30738..330955592650 100644 --- a/docs/source/en/model_doc/sam2_video.md +++ b/docs/source/en/model_doc/sam2_video.md @@ -13,6 +13,10 @@ specific language governing permissions and limitations under the License. rendered properly in your Markdown viewer. --> +*This model was released on 2024-07-29 and added to Hugging Face Transformers on 2025-08-14.* + +# SAM2 Video +
PyTorch @@ -21,8 +25,6 @@ rendered properly in your Markdown viewer.
-# SAM2 Video - ## Overview SAM2 (Segment Anything Model 2) was proposed in [Segment Anything in Images and Videos](https://ai.meta.com/research/publications/sam-2-segment-anything-in-images-and-videos/) by Nikhila Ravi, Valentin Gabeur, Yuan-Ting Hu, Ronghang Hu, Chaitanya Ryali, Tengyu Ma, Haitham Khedr, Roman Rädle, Chloe Rolland, Laura Gustafson, Eric Mintun, Junting Pan, Kalyan Vasudev Alwala, Nicolas Carion, Chao-Yuan Wu, Ross Girshick, Piotr Dollár, Christoph Feichtenhofer.