Add documented support for object detection w/ DETR

README.md

@@ -6,7 +6,7 @@
 [![license](https://img.shields.io/github/license/xenova/transformers.js)](https://github.com/xenova/transformers.js/blob/main/LICENSE)
 
 
-Run 🤗 Transformers in your browser! We currently support [BERT](https://huggingface.co/docs/transformers/model_doc/bert), [ALBERT](https://huggingface.co/docs/transformers/model_doc/albert), [DistilBERT](https://huggingface.co/docs/transformers/model_doc/distilbert), [T5](https://huggingface.co/docs/transformers/model_doc/t5), [T5v1.1](https://huggingface.co/docs/transformers/model_doc/t5v1.1), [FLAN-T5](https://huggingface.co/docs/transformers/model_doc/flan-t5), [GPT2](https://huggingface.co/docs/transformers/model_doc/gpt2), [BART](https://huggingface.co/docs/transformers/model_doc/bart), [CodeGen](https://huggingface.co/docs/transformers/model_doc/codegen), [Whisper](https://huggingface.co/docs/transformers/model_doc/whisper), [CLIP](https://huggingface.co/docs/transformers/model_doc/clip), [Vision Transformer](https://huggingface.co/docs/transformers/model_doc/vit), and [VisionEncoderDecoder](https://huggingface.co/docs/transformers/model_doc/vision-encoder-decoder) models, for a variety of tasks including: masked language modelling, text classification, text-to-text generation, translation, summarization, question answering, text generation, automatic speech recognition, image classification, zero-shot image classification, and image-to-text.
+Run 🤗 Transformers in your browser! We currently support [BERT](https://huggingface.co/docs/transformers/model_doc/bert), [ALBERT](https://huggingface.co/docs/transformers/model_doc/albert), [DistilBERT](https://huggingface.co/docs/transformers/model_doc/distilbert), [T5](https://huggingface.co/docs/transformers/model_doc/t5), [T5v1.1](https://huggingface.co/docs/transformers/model_doc/t5v1.1), [FLAN-T5](https://huggingface.co/docs/transformers/model_doc/flan-t5), [GPT2](https://huggingface.co/docs/transformers/model_doc/gpt2), [BART](https://huggingface.co/docs/transformers/model_doc/bart), [CodeGen](https://huggingface.co/docs/transformers/model_doc/codegen), [Whisper](https://huggingface.co/docs/transformers/model_doc/whisper), [CLIP](https://huggingface.co/docs/transformers/model_doc/clip), [Vision Transformer](https://huggingface.co/docs/transformers/model_doc/vit), [VisionEncoderDecoder](https://huggingface.co/docs/transformers/model_doc/vision-encoder-decoder), and [DETR](https://huggingface.co/docs/transformers/model_doc/detr) models, for a variety of tasks including: masked language modelling, text classification, text-to-text generation, translation, summarization, question answering, text generation, automatic speech recognition, image classification, zero-shot image classification, image-to-text, and object detection.
 
 ![teaser](https://user-images.githubusercontent.com/26504141/221056008-e906614e-e6f0-4e10-b0a8-7d5c99e955b4.gif)
 

index.html

@@ -752,6 +752,17 @@ env.onnx.wasm.wasmPaths = '/path/to/files/';</code></pre>
                             </a>.
                         </div>
                     </li>
+                    <li class="list-group-item d-flex justify-content-between align-items-start">
+                        <div class="ms-2 me-auto">
+                            <div class="fw-bold">object-detection</div>
+                            Supported models: <code>facebook/detr-resnet-50</code>,
+                            <code>facebook/detr-resnet-101</code>.
+                            For more information, check out the
+                            <a href="https://huggingface.co/tasks/object-detection">
+                                Object detection docs
+                            </a>.
+                        </div>
+                    </li>
                     <li class="list-group-item d-flex justify-content-between align-items-start">
                         <div class="ms-2 me-auto">
                             <div class="fw-bold">embeddings</div>
@@ -905,6 +916,15 @@ env.onnx.wasm.wasmPaths = '/path/to/files/';</code></pre>
                                 Encoder Decoder Models docs</a>.
                         </div>
                     </li>
+                    <li class="list-group-item d-flex justify-content-between align-items-start">
+                        <div class="ms-2 me-auto">
+                            <div class="fw-bold">DETR</div>
+                            Tasks: Object detection
+                            <code>(AutoModelForObjectDetection)</code>.
+                            For more information, check out the <a
+                                href="https://huggingface.co/docs/transformers/model_doc/detr">DETR docs</a>.
+                        </div>
+                    </li>
                 </ol>
                 <br>
                 <p class="mb-2">Don't see your model type or task supported? Raise an

package.json

@@ -1,7 +1,7 @@
 {
   "name": "@xenova/transformers",
   "version": "1.3.2",
-  "description": "Run 🤗 Transformers in your browser! We currently support BERT, ALBERT, DistilBERT, T5, T5v1.1, FLAN-T5, GPT2, BART, CodeGen, Whisper, CLIP, Vision Transformer, and VisionEncoderDecoder models, for a variety of tasks including: masked language modelling, text classification, text-to-text generation, translation, summarization, question answering, text generation, automatic speech recognition, image classification, zero-shot image classification, and image-to-text.",
+  "description": "Run 🤗 Transformers in your browser! We currently support BERT, ALBERT, DistilBERT, T5, T5v1.1, FLAN-T5, GPT2, BART, CodeGen, Whisper, CLIP, Vision Transformer, VisionEncoderDecoder, and DETR models, for a variety of tasks including: masked language modelling, text classification, text-to-text generation, translation, summarization, question answering, text generation, automatic speech recognition, image classification, zero-shot image classification, image-to-text, and object detection.",
   "main": "./src/transformers.js",
   "directories": {
     "test": "tests"