@huggingface/transformers/src/models/roformer/modeling_roformer.js

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import { PreTrainedModel } from '../modeling_utils.js';
import {
    QuestionAnsweringModelOutput,
    SequenceClassifierOutput,
    TokenClassifierOutput,
    MaskedLMOutput,
} from '../modeling_outputs.js';

export class RoFormerPreTrainedModel extends PreTrainedModel {}

/**
 * The bare RoFormer Model transformer outputting raw hidden-states without any specific head on top.
 */
export class RoFormerModel extends RoFormerPreTrainedModel {}

/**
 * RoFormer Model with a `language modeling` head on top.
 */
export class RoFormerForMaskedLM extends RoFormerPreTrainedModel {
    /**
     * Calls the model on new inputs.
     *
     * @param {Object} model_inputs The inputs to the model.
     * @returns {Promise<MaskedLMOutput>} An object containing the model's output logits for masked language modeling.
     */
    async _call(model_inputs) {
        return new MaskedLMOutput(await super._call(model_inputs));
    }
}

/**
 * RoFormer Model transformer with a sequence classification/regression head on top (a linear layer on top of the pooled output)
 */
export class RoFormerForSequenceClassification extends RoFormerPreTrainedModel {
    /**
     * Calls the model on new inputs.
     *
     * @param {Object} model_inputs The inputs to the model.
     * @returns {Promise<SequenceClassifierOutput>} An object containing the model's output logits for sequence classification.
     */
    async _call(model_inputs) {
        return new SequenceClassifierOutput(await super._call(model_inputs));
    }
}

/**
 * RoFormer Model with a token classification head on top (a linear layer on top of the hidden-states output)
 * e.g. for Named-Entity-Recognition (NER) tasks.
 */
export class RoFormerForTokenClassification extends RoFormerPreTrainedModel {
    /**
     * Calls the model on new inputs.
     *
     * @param {Object} model_inputs The inputs to the model.
     * @returns {Promise<TokenClassifierOutput>} An object containing the model's output logits for token classification.
     */
    async _call(model_inputs) {
        return new TokenClassifierOutput(await super._call(model_inputs));
    }
}

/**
 * RoFormer Model with a span classification head on top for extractive question-answering tasks like SQuAD
 * (a linear layers on top of the hidden-states output to compute `span start logits` and `span end logits`).
 */
export class RoFormerForQuestionAnswering extends RoFormerPreTrainedModel {
    /**
     * Calls the model on new inputs.
     *
     * @param {Object} model_inputs The inputs to the model.
     * @returns {Promise<QuestionAnsweringModelOutput>} An object containing the model's output logits for question answering.
     */
    async _call(model_inputs) {
        return new QuestionAnsweringModelOutput(await super._call(model_inputs));
    }
}
// TODO: Add RoFormerForCausalLM and RoFormerForMultipleChoice