Add support for D-FINE

README.md

@@ -306,6 +306,7 @@ You can refine your search by selecting the task you're interested in (e.g., [te
 1. **[ConvBERT](https://huggingface.co/docs/transformers/model_doc/convbert)** (from YituTech) released with the paper [ConvBERT: Improving BERT with Span-based Dynamic Convolution](https://arxiv.org/abs/2008.02496) by Zihang Jiang, Weihao Yu, Daquan Zhou, Yunpeng Chen, Jiashi Feng, Shuicheng Yan.
 1. **[ConvNeXT](https://huggingface.co/docs/transformers/model_doc/convnext)** (from Facebook AI) released with the paper [A ConvNet for the 2020s](https://arxiv.org/abs/2201.03545) by Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, Saining Xie.
 1. **[ConvNeXTV2](https://huggingface.co/docs/transformers/model_doc/convnextv2)** (from Facebook AI) released with the paper [ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders](https://arxiv.org/abs/2301.00808) by Sanghyun Woo, Shoubhik Debnath, Ronghang Hu, Xinlei Chen, Zhuang Liu, In So Kweon, Saining Xie.
+1. **[D-FINE](https://huggingface.co/docs/transformers/model_doc/d_fine)** (from University of Science and Technology of China) released with the paper [D-FINE: Redefine Regression Task in DETRs as Fine-grained Distribution Refinement](https://arxiv.org/abs/2410.13842) by Yansong Peng, Hebei Li, Peixi Wu, Yueyi Zhang, Xiaoyan Sun, Feng Wu.
 1. **[DAC](https://huggingface.co/docs/transformers/model_doc/dac)** (from Descript) released with the paper [Descript Audio Codec: High-Fidelity Audio Compression with Improved RVQGAN](https://arxiv.org/abs/2306.06546) by Rithesh Kumar, Prem Seetharaman, Alejandro Luebs, Ishaan Kumar, Kundan Kumar.
 1. **[DeBERTa](https://huggingface.co/docs/transformers/model_doc/deberta)** (from Microsoft) released with the paper [DeBERTa: Decoding-enhanced BERT with Disentangled Attention](https://arxiv.org/abs/2006.03654) by Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen.
 1. **[DeBERTa-v2](https://huggingface.co/docs/transformers/model_doc/deberta-v2)** (from Microsoft) released with the paper [DeBERTa: Decoding-enhanced BERT with Disentangled Attention](https://arxiv.org/abs/2006.03654) by Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen.

docs/snippets/6_supported-models.snippet

@@ -20,6 +20,7 @@
 1. **[ConvBERT](https://huggingface.co/docs/transformers/model_doc/convbert)** (from YituTech) released with the paper [ConvBERT: Improving BERT with Span-based Dynamic Convolution](https://arxiv.org/abs/2008.02496) by Zihang Jiang, Weihao Yu, Daquan Zhou, Yunpeng Chen, Jiashi Feng, Shuicheng Yan.
 1. **[ConvNeXT](https://huggingface.co/docs/transformers/model_doc/convnext)** (from Facebook AI) released with the paper [A ConvNet for the 2020s](https://arxiv.org/abs/2201.03545) by Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, Saining Xie.
 1. **[ConvNeXTV2](https://huggingface.co/docs/transformers/model_doc/convnextv2)** (from Facebook AI) released with the paper [ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders](https://arxiv.org/abs/2301.00808) by Sanghyun Woo, Shoubhik Debnath, Ronghang Hu, Xinlei Chen, Zhuang Liu, In So Kweon, Saining Xie.
+1. **[D-FINE](https://huggingface.co/docs/transformers/model_doc/d_fine)** (from University of Science and Technology of China) released with the paper [D-FINE: Redefine Regression Task in DETRs as Fine-grained Distribution Refinement](https://arxiv.org/abs/2410.13842) by Yansong Peng, Hebei Li, Peixi Wu, Yueyi Zhang, Xiaoyan Sun, Feng Wu.
 1. **[DAC](https://huggingface.co/docs/transformers/model_doc/dac)** (from Descript) released with the paper [Descript Audio Codec: High-Fidelity Audio Compression with Improved RVQGAN](https://arxiv.org/abs/2306.06546) by Rithesh Kumar, Prem Seetharaman, Alejandro Luebs, Ishaan Kumar, Kundan Kumar.
 1. **[DeBERTa](https://huggingface.co/docs/transformers/model_doc/deberta)** (from Microsoft) released with the paper [DeBERTa: Decoding-enhanced BERT with Disentangled Attention](https://arxiv.org/abs/2006.03654) by Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen.
 1. **[DeBERTa-v2](https://huggingface.co/docs/transformers/model_doc/deberta-v2)** (from Microsoft) released with the paper [DeBERTa: Decoding-enhanced BERT with Disentangled Attention](https://arxiv.org/abs/2006.03654) by Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen.

src/models.js

@@ -5257,6 +5257,19 @@ export class RFDetrForObjectDetection extends RFDetrPreTrainedModel {
 export class RFDetrObjectDetectionOutput extends RTDetrObjectDetectionOutput { }
 //////////////////////////////////////////////////
 
+//////////////////////////////////////////////////
+export class DFinePreTrainedModel extends PreTrainedModel { }
+export class DFineModel extends DFinePreTrainedModel { }
+export class DFineForObjectDetection extends DFinePreTrainedModel {
+    /**
+     * @param {any} model_inputs
+     */
+    async _call(model_inputs) {
+        return new RTDetrObjectDetectionOutput(await super._call(model_inputs));
+    }
+}
+//////////////////////////////////////////////////
+
 //////////////////////////////////////////////////
 export class TableTransformerPreTrainedModel extends PreTrainedModel { }
 
@@ -7566,6 +7579,7 @@ const MODEL_MAPPING_NAMES_ENCODER_ONLY = new Map([
     ['rt_detr', ['RTDetrModel', RTDetrModel]],
     ['rt_detr_v2', ['RTDetrV2Model', RTDetrV2Model]],
     ['rf_detr', ['RFDetrModel', RFDetrModel]],
+    ['d_fine', ['DFineModel', DFineModel]],
     ['table-transformer', ['TableTransformerModel', TableTransformerModel]],
     ['vit', ['ViTModel', ViTModel]],
     ['ijepa', ['IJepaModel', IJepaModel]],
@@ -7869,6 +7883,7 @@ const MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES = new Map([
     ['rt_detr', ['RTDetrForObjectDetection', RTDetrForObjectDetection]],
     ['rt_detr_v2', ['RTDetrV2ForObjectDetection', RTDetrV2ForObjectDetection]],
     ['rf_detr', ['RFDetrForObjectDetection', RFDetrForObjectDetection]],
+    ['d_fine', ['DFineForObjectDetection', DFineForObjectDetection]],
     ['table-transformer', ['TableTransformerForObjectDetection', TableTransformerForObjectDetection]],
     ['yolos', ['YolosForObjectDetection', YolosForObjectDetection]],
 ]);