Added curated spaces to tasks (#589)

merveenoyan · web-flow · commit ff1a2d71aa72 · 2023-01-04T11:00:34.000+03:00
* added curated spaces

* Added more apps!
diff --git a/tasks/src/audio-classification/data.ts b/tasks/src/audio-classification/data.ts
@@ -58,7 +58,12 @@ const taskData: TaskDataCustom = {
 			id:          "superb/hubert-large-superb-er",
 		},
 	],
-	spaces:  [],
+	spaces:  [
+		{
+			description: "An application that can predict the language spoken in a given audio.",
+			id:          "akhaliq/Speechbrain-audio-classification",
+		},
+	],
 	summary:
 		"Audio classification is the task of assigning a label or class to a given audio. It can be used for recognizing which command a user is giving or the emotion of a statement, as well as identifying a speaker.",
 	widgetModels: ["speechbrain/google_speech_command_xvector"],
diff --git a/tasks/src/audio-to-audio/data.ts b/tasks/src/audio-to-audio/data.ts
@@ -41,7 +41,16 @@ const taskData: TaskDataCustom = {
 			id:          "speechbrain/metricgan-plus-voicebank",
 		},
 	],
-	spaces:       [],
+	spaces:       [
+		{
+			description: "An application that can separate speech.",
+			id:          "akhaliq/speechbrain-speech-seperation",
+		},
+		{
+			description: "An application that can translate from speech to speech between Hokkien and English.",
+			id:          "facebook/Hokkien_Translation",
+		},
+	],
 	summary:      "Audio-to-Audio is a family of tasks in which the input is an audio and the output is one or multiple generated audios. Some example tasks are speech enhancement and source separation.",
 	widgetModels: ["speechbrain/sepformer-wham"],
 	youtubeId:    "iohj7nCCYoM",
diff --git a/tasks/src/automatic-speech-recognition/data.ts b/tasks/src/automatic-speech-recognition/data.ts
@@ -51,7 +51,16 @@ const taskData: TaskDataCustom = {
 			id:          "facebook/s2t-small-mustc-en-fr-st",
 		},
 	],
-	spaces:       [],
+	spaces:       [
+		{
+			description: "A powerful general-purpose speech recognition application.",
+			id:          "openai/whisper",
+		},
+		{
+			description: "An application that transcribes speeches in YouTube videos.",
+			id:          "jeffistyping/Youtube-Whisperer",
+		},
+	],
 	summary:      "Automatic Speech Recognition (ASR), also known as Speech to Text (STT), is the task of transcribing a given audio to text. It has many applications, such as voice user interfaces.",
 	widgetModels: ["facebook/wav2vec2-base-960h"],
 	youtubeId:    "TksaY_FDgnk",
diff --git a/tasks/src/conversational/data.ts b/tasks/src/conversational/data.ts
@@ -48,7 +48,12 @@ const taskData: TaskDataCustom = {
 			id:          "microsoft/DialoGPT-large",
 		},
 	],
-	spaces:       [],
+	spaces:       [
+		{
+			description: "A chatbot based on Blender model.",
+			id:          "EXFINITE/BlenderBot-UI",
+		},
+	],
 	summary:      "Conversational response modelling is the task of generating conversational text that is relevant, coherent and knowledgable given a prompt. These models have applications in chatbots, and as a part of voice assistants",
 	widgetModels: ["facebook/blenderbot-400M-distill"],
 	youtubeId:    "",
diff --git a/tasks/src/depth-estimation/data.ts b/tasks/src/depth-estimation/data.ts
@@ -29,7 +29,16 @@ const taskData: TaskDataCustom = {
 			id:          "vinvino02/glpn-kitti",
 		},
 	],
-	spaces:       [],
+	spaces:       [
+		{
+			description: "An application that predicts the depth of an image and then reconstruct the 3D model as voxels.",
+			id:          "radames/dpt-depth-estimation-3d-voxels",
+		},
+		{
+			description: "An application that can estimate the depth in a given image.",
+			id:          "keras-io/Monocular-Depth-Estimation",
+		},
+	],
 	summary:      "Depth estimation is the task of predicting depth of the objects present in an image.",
 	widgetModels: [""],
 	youtubeId:    "",
diff --git a/tasks/src/document-question-answering/data.ts b/tasks/src/document-question-answering/data.ts
@@ -48,7 +48,16 @@ const taskData: TaskDataCustom = {
 			id:          "naver-clova-ix/donut-base-finetuned-docvqa",
 		},
 	],
-	spaces:       [],
+	spaces:       [
+		{
+			description: "A robust document question answering application.",
+			id:          "impira/docquery",
+		},
+		{
+			description: "An application that can answer questions from invoices.",
+			id:          "impira/invoices",
+		},
+	],
 	summary:      "Document Question Answering (also known as Document Visual Question Answering) is the task of answering questions on document images. Document question answering models take a (document, question) pair as input and return an answer in natural language. Models usually rely on multi-modal features, combining text, position of words (bounding-boxes) and image.",
 	widgetModels: ["impira/layoutlm-document-qa"],
 	youtubeId:    "",
diff --git a/tasks/src/image-classification/data.ts b/tasks/src/image-classification/data.ts
@@ -71,7 +71,13 @@ const taskData: TaskDataCustom = {
 			id:          "facebook/deit-base-distilled-patch16-224",
 		},
 	],
-	spaces:       [],
+	spaces:       [
+		{
+			// TO DO: write description
+			description: "An application that classifies what a given image is about.",
+			id:          "nielsr/perceiver-image-classification",
+		},
+	],
 	summary:      "Image classification is the task of assigning a label or class to an entire image. Images are expected to have only one class for each image. Image classification models take an image as input and return a prediction about which class the image belongs to.",
 	widgetModels: ["google/vit-base-patch16-224"],
 	youtubeId:    "tjAIM7BOYhw",
diff --git a/tasks/src/image-segmentation/data.ts b/tasks/src/image-segmentation/data.ts
@@ -50,7 +50,16 @@ const taskData: TaskDataCustom = {
 			id:          "microsoft/beit-large-finetuned-ade-640-640",
 		},
 	],
-	spaces:       [],
+	spaces:       [
+		{
+			description: "A semantic segmentation application that can predict unseen instances out of the box.",
+			id:          "facebook/ov-seg",
+		},
+		{
+			description: "A semantic segmentation application that predicts human silhouettes.",
+			id:          "keras-io/Human-Part-Segmentation",
+		},
+	],
 	summary:      "Image Segmentation divides an image into segments where each pixel in the image is mapped to an object. This task has multiple variants such as instance segmentation, panoptic segmentation and semantic segmentation.",
 	widgetModels: ["facebook/detr-resnet-50-panoptic"],
 	youtubeId:    "dKE8SIt9C-w",
diff --git a/tasks/src/image-to-image/data.ts b/tasks/src/image-to-image/data.ts
@@ -54,7 +54,24 @@ const taskData: TaskDataCustom = {
 			id:          "lambdalabs/sd-image-variations-diffusers",
 		},
 	],
-	spaces:       [],
+	spaces:       [
+		{
+			description: "Image enhancer application for low light.",
+			id:          "keras-io/low-light-image-enhancement",
+		},
+		{
+			description: "Style transfer application.",
+			id:          "keras-io/neural-style-transfer",
+		},
+		{
+			description: "An application that prettifies your drawings.",
+			id:          "huggingface-projects/diffuse-the-rest",
+		},
+		{
+			description: "Image colorization application for anime drawings.",
+			id:          "Gradio-Blocks/anime-colorization",
+		},
+	],
 	summary:      "Image to image is the task of transforming a source image to match the characteristics of a target image or a target image domain. Any image manipulation and enhancement is possible with image to image models.",
 	widgetModels: [""],
 	youtubeId:    "",
diff --git a/tasks/src/image-to-text/data.ts b/tasks/src/image-to-text/data.ts
@@ -49,7 +49,20 @@ const taskData: TaskDataCustom = {
 			id:          "nlpconnect/vit-gpt2-image-captioning",
 		},
 	],
-	spaces:       [],
+	spaces:       [
+		{
+			description: "A robust image captioning application.",
+			id:          "flax-community/image-captioning",
+		},
+		{
+			description: "An application that transcribes handwritings into text.",
+			id:          "nielsr/TrOCR-handwritten",
+		},
+		{
+			description: "An application that can caption images and answer questions about a given image.",
+			id:          "Salesforce/BLIP",
+		},
+	],
 	summary:      "",
 	widgetModels: ["nlpconnect/vit-gpt2-image-captioning"],
 	youtubeId:    "",
diff --git a/tasks/src/object-detection/data.ts b/tasks/src/object-detection/data.ts
@@ -47,7 +47,20 @@ const taskData: TaskDataCustom = {
 			id:          "microsoft/beit-base-patch16-224-pt22k-ft22k",
 		},
 	],
-	spaces:       [],
+	spaces:       [
+		{
+			description: "An object detection application that can detect unseen objects out of the box.",
+			id:          "adirik/OWL-ViT",
+		},
+		{
+			description: "An object detection application that can detect facemasks in an image.",
+			id:          "nickmuchi/Face-Mask-Detection-with-YOLOS",
+		},
+		{
+			description: "An application that contains various object detection models to try from.",
+			id:          "Gradio-Blocks/Object-Detection-With-DETR-and-YOLOS",
+		},
+	],
 	summary:      "Object Detection models allow users to identify objects of certain defined classes. Object detection models receive an image as input and output the images with bounding boxes and labels on detected objects.",
 	widgetModels: ["facebook/detr-resnet-50"],
 	youtubeId:    "WdAeKSOpxhw",
diff --git a/tasks/src/question-answering/data.ts b/tasks/src/question-answering/data.ts
@@ -54,7 +54,12 @@ const taskData: TaskDataCustom = {
 			id:          "google/tapas-base-finetuned-wtq",
 		},
 	],
-	spaces:       [],
+	spaces:       [
+		{
+			description: "An application that can answer a long question from Wikipedia.",
+			id:          "deepset/wikipedia-assistant",
+		},
+	],
 	summary:      "Question Answering models can retrieve the answer to a question from a given text, which is useful for searching for an answer in a document. Some question answering models can generate answers without context!",
 	widgetModels: ["deepset/roberta-base-squad2"],
 	youtubeId:    "ajPx5LwJD-I",
diff --git a/tasks/src/reinforcement-learning/data.ts b/tasks/src/reinforcement-learning/data.ts
@@ -59,7 +59,16 @@ const taskData: TaskDataCustom = {
 			id: "HumanCompatibleAI/ppo-seals-CartPole-v0",
 		},
 	],
-	spaces:  [],
+	spaces:  [
+		{
+			description: "An application for a cute puppy agent learning to catch a stick.",
+			id:          "ThomasSimonini/Huggy",
+		},
+		{
+			description: "An application to play Snowball Fight with a reinforcement learning agent.",
+			id:          "ThomasSimonini/SnowballFight",
+		},
+	],
 	summary:
 		"Reinforcement learning is the computational approach of learning from action by interacting with an environment through trial and error and receiving rewards (negative or positive) as feedback",
 	widgetModels: [],
diff --git a/tasks/src/sentence-similarity/data.ts b/tasks/src/sentence-similarity/data.ts
@@ -74,7 +74,24 @@ const taskData: TaskDataCustom = {
 			id:          "clips/mfaq",
 		},
 	],
-	spaces:       [],
+	spaces:       [
+		{
+			description: "An application that leverages sentence similarity to answer questions from YouTube videos.",
+			id:          "Gradio-Blocks/Ask_Questions_To_YouTube_Videos",
+		},
+		{
+			description: "An application that retrieves relevant PubMed abstracts for a given online article which can be used as further references.",
+			id:          "Gradio-Blocks/pubmed-abstract-retriever",
+		},
+		{
+			description: "An application that leverages sentence similarity to summarize text.",
+			id:          "nickmuchi/article-text-summarizer",
+		},
+		{
+			description: "A guide that explains how Sentence Transformers can be used for semantic search.",
+			id:          "sentence-transformers/Sentence_Transformers_for_semantic_search",
+		},
+	],
 	summary:      "Sentence Similarity is the task of determining how similar two texts are. Sentence similarity models convert input texts into vectors (embeddings) that capture semantic information and calculate how close (similar) they are between them. This task is particularly useful for information retrieval and clustering/grouping.",
 	widgetModels: ["sentence-transformers/all-MiniLM-L6-v2"],
 	youtubeId:    "VCZq5AkbNEU",
diff --git a/tasks/src/summarization/data.ts b/tasks/src/summarization/data.ts
@@ -46,7 +46,24 @@ const taskData: TaskDataCustom = {
 			id:          "google/bigbird-pegasus-large-pubmed",
 		},
 	],
-	spaces:       [],
+	spaces:       [
+		{
+			description: "An application that can summarize long paragraphs.",
+			id:          "pszemraj/summarize-long-text",
+		},
+		{
+			description: "A much needed summarization application for terms and conditions.",
+			id:          "ml6team/distilbart-tos-summarizer-tosdr",
+		},
+		{
+			description: "An application that summarizes long documents.",
+			id:          "pszemraj/document-summarization",
+		},
+		{
+			description: "An application that can detect errors in abstractive summarization.",
+			id:          "ml6team/post-processing-summarization",
+		},
+	],
 	summary:      "Summarization is the task of producing a shorter version of a document while preserving its important information. Some models can extract text from the original input, while other models can generate entirely new text.",
 	widgetModels: ["sshleifer/distilbart-cnn-12-6"],
 	youtubeId:    "yHnr5Dk2zCI",
diff --git a/tasks/src/table-question-answering/data.ts b/tasks/src/table-question-answering/data.ts
@@ -48,7 +48,13 @@ const taskData: TaskDataCustom = {
 
 			},
 		],
-	spaces:       [],
+	spaces:       [
+		{
+			description: "An application that answers questions based on table CSV files.",
+			id:          "katanaml/table-query",
+
+		},
+	],
 	summary:      "Table Question Answering (Table QA) is the answering a question about an information on a given table.",
 	widgetModels: ["google/tapas-base-finetuned-wtq"],
 };
diff --git a/tasks/src/tabular-classification/data.ts b/tasks/src/tabular-classification/data.ts
@@ -56,7 +56,16 @@ const taskData: TaskData = {
 			id:          "scikit-learn/cancer-prediction-trees",
 		},
 	],
-	spaces:  [],
+	spaces:  [
+		{
+			description: "An application that can predict defective products on a production line.",
+			id:          "scikit-learn/tabular-playground",
+		},
+		{
+			description: "An application that compares various tabular classification techniques on different datasets.",
+			id:          "scikit-learn/classification",
+		},
+	],
 	summary:
 		"Tabular classification is the task of classifying a target category (a group) based on set of attributes.",
 	widgetModels: ["scikit-learn/tabular-playground"],
diff --git a/tasks/src/tabular-regression/data.ts b/tasks/src/tabular-regression/data.ts
@@ -49,7 +49,12 @@ const taskData: TaskData = {
 			id:          "scikit-learn/Fish-Weight",
 		},
 	],
-	spaces:  [],
+	spaces:  [
+		{
+			description: "An application that can predict weight of a fish based on set of attributes.",
+			id:          "scikit-learn/fish-weight-prediction",
+		},
+	],
 	summary:
 		"Tabular regression is the task of predicting a numerical value given a set of attributes.",
 	widgetModels: ["scikit-learn/Fish-Weight"],
diff --git a/tasks/src/text-classification/data.ts b/tasks/src/text-classification/data.ts
@@ -69,7 +69,20 @@ const taskData: TaskDataCustom = {
 			id:          "roberta-large-mnli",
 		},
 	],
-	spaces:       [],
+	spaces:       [
+		{
+			description: "An application that can classify financial sentiment.",
+			id:          "IoannisTr/Tech_Stocks_Trading_Assistant",
+		},
+		{
+			description: "A dashboard that contains various text classification tasks.",
+			id:          "miesnerjacob/Multi-task-NLP",
+		},
+		{
+			description: "An application that analyzes user reviews in healthcare.",
+			id:          "spacy/healthsea-demo",
+		},
+	],
 	summary:      "Text Classification is the task of assigning a label or class to a given text. Some use cases are sentiment analysis, natural language inference, and assessing grammatical correctness.",
 	widgetModels: ["distilbert-base-uncased-finetuned-sst-2-english"],
 	youtubeId:    "leNG9fN9FQU",
diff --git a/tasks/src/text-generation/data.ts b/tasks/src/text-generation/data.ts
@@ -50,7 +50,16 @@ const taskData: TaskDataCustom = {
 			id:          "bigscience/T0pp",
 		},
 	],
-	spaces:       [],
+	spaces:       [
+		{
+			description: "A robust text generation model that can perform various tasks through natural language prompting.",
+			id:          "huggingface/bloom_demo",
+		},
+		{
+			description: "An text generation based application that can write code for Python, Java & JavaScript.",
+			id:          "bigcode/santacoder-demo",
+		},
+	],
 	summary:      "Generating text is the task of producing new text. These models can, for example, fill in incomplete text or paraphrase.",
 	widgetModels: ["gpt2"],
 	youtubeId:    "Vpjb1lu0MDk",
diff --git a/tasks/src/text-to-image/data.ts b/tasks/src/text-to-image/data.ts
@@ -37,7 +37,12 @@ const taskData: TaskDataCustom = {
 			id:          "CompVis/stable-diffusion-v1-4",
 		},
 	],
-	spaces:       [],
+	spaces:       [
+		{
+			description: "A powerful text-to-image application",
+			id:          "stabilityai/stable-diffusion",
+		},
+	],
 	summary:      "Generates images from input text. These models can be used to generate and modify images based on text prompts.",
 	widgetModels: ["CompVis/stable-diffusion-v1-4"],
 	youtubeId:    "",
diff --git a/tasks/src/text-to-speech/data.ts b/tasks/src/text-to-speech/data.ts
diff --git a/tasks/src/token-classification/data.ts b/tasks/src/token-classification/data.ts
diff --git a/tasks/src/translation/data.ts b/tasks/src/translation/data.ts
diff --git a/tasks/src/unconditional-image-generation/data.ts b/tasks/src/unconditional-image-generation/data.ts
diff --git a/tasks/src/video-classification/data.ts b/tasks/src/video-classification/data.ts
diff --git a/tasks/src/visual-question-answering/data.ts b/tasks/src/visual-question-answering/data.ts
diff --git a/tasks/src/zero-shot-image-classification/data.ts b/tasks/src/zero-shot-image-classification/data.ts
