Build, train and deploy state of the art models powered by the reference open source in machine learning.
Want to have a nice know-it-all bot that can answer any question?. This action allows you to ask a question and get an answer from a trained model. See the docs
Convert an object to a JSON format string
This task reads some image input and outputs the likelihood of classes. This action allows you to classify images into categories. See the docs
This task is well known to translate text from one language to another. See the docs
The Hugging Face API provides access to a vast range of machine learning models, primarily for natural language processing (NLP) tasks like text classification, translation, summarization, and question answering. It lets you leverage pre-trained models and fine-tune them on your data. Using the API within Pipedream, you can automate workflows that involve language processing, integrate AI insights into your apps, or respond to events with AI-generated content.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
hugging_face: {
type: "app",
app: "hugging_face",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://huggingface.co/api/whoami-v2`,
headers: {
Authorization: `Bearer ${this.hugging_face.$auth.access_token}`,
},
})
},
})
The Pipedream Utils app is a set of pre-built functions that streamline common tasks in your workflows. It acts like a Swiss Army knife for developers, providing essential tools such as format conversion, date manipulation, and text processing. By leveraging these functions, you can reduce the boilerplate code needed for routine operations, speeding up the development of intricate automations. The Helper Functions API can be a game changer when it comes to tasks like parsing dates in user-friendly formats, encoding and decoding data, or generating UUIDs, making them more efficient and less error-prone.
export default defineComponent({
props: {
pipedream_utils: {
type: "app",
app: "pipedream_utils",
}
},
async run({steps, $}) {
},
})