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import type { TaskDataCustom } from "../Types"; | |
const taskData: TaskDataCustom = { | |
datasets: [ | |
{ | |
description: | |
"A dataset of 7k conversations explicitly designed to exhibit multiple conversation modes: displaying personality, having empathy, and demonstrating knowledge.", | |
id: "blended_skill_talk", | |
}, | |
{ | |
description: | |
"ConvAI is a dataset of human-to-bot conversations labeled for quality. This data can be used to train a metric for evaluating dialogue systems", | |
id: "conv_ai_2", | |
}, | |
{ | |
description: "EmpatheticDialogues, is a dataset of 25k conversations grounded in emotional situations", | |
id: "empathetic_dialogues", | |
}, | |
], | |
demo: { | |
inputs: [ | |
{ | |
label: "Input", | |
content: "Hey my name is Julien! How are you?", | |
type: "text", | |
}, | |
], | |
outputs: [ | |
{ | |
label: "Answer", | |
content: "Hi Julien! My name is Julia! I am well.", | |
type: "text", | |
}, | |
], | |
}, | |
metrics: [ | |
{ | |
description: | |
"BLEU score is calculated by counting the number of shared single or subsequent tokens between the generated sequence and the reference. Subsequent n tokens are called “n-grams”. Unigram refers to a single token while bi-gram refers to token pairs and n-grams refer to n subsequent tokens. The score ranges from 0 to 1, where 1 means the translation perfectly matched and 0 did not match at all", | |
id: "bleu", | |
}, | |
], | |
models: [ | |
{ | |
description: "A faster and smaller model than the famous BERT model.", | |
id: "facebook/blenderbot-400M-distill", | |
}, | |
{ | |
description: | |
"DialoGPT is a large-scale pretrained dialogue response generation model for multiturn conversations.", | |
id: "microsoft/DialoGPT-large", | |
}, | |
], | |
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: "", | |
}; | |
export default taskData; | |