@huggingface/inference
Version:
Typescript client for the Hugging Face Inference Providers and Inference Endpoints
40 lines (39 loc) • 1.69 kB
JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
exports.zeroShotImageClassification = zeroShotImageClassification;
const getInferenceProviderMapping_js_1 = require("../../lib/getInferenceProviderMapping.js");
const getProviderHelper_js_1 = require("../../lib/getProviderHelper.js");
const base64FromBytes_js_1 = require("../../utils/base64FromBytes.js");
const request_js_1 = require("../../utils/request.js");
async function preparePayload(args) {
if (args.inputs instanceof Blob) {
return {
...args,
inputs: {
image: (0, base64FromBytes_js_1.base64FromBytes)(new Uint8Array(await args.inputs.arrayBuffer())),
},
};
}
else {
return {
...args,
inputs: {
image: (0, base64FromBytes_js_1.base64FromBytes)(new Uint8Array(args.inputs.image instanceof ArrayBuffer ? args.inputs.image : await args.inputs.image.arrayBuffer())),
},
};
}
}
/**
* Classify an image to specified classes.
* Recommended model: openai/clip-vit-large-patch14-336
*/
async function zeroShotImageClassification(args, options) {
const provider = await (0, getInferenceProviderMapping_js_1.resolveProvider)(args.provider, args.model, args.endpointUrl);
const providerHelper = (0, getProviderHelper_js_1.getProviderHelper)(provider, "zero-shot-image-classification");
const payload = await preparePayload(args);
const { data: res } = await (0, request_js_1.innerRequest)(payload, providerHelper, {
...options,
task: "zero-shot-image-classification",
});
return providerHelper.getResponse(res);
}