transformers.js/tests/models/helium/test_modeling_helium.js

import { PreTrainedTokenizer, HeliumForCausalLM } from "../../../src/transformers.js";

import { MAX_MODEL_LOAD_TIME, MAX_TEST_EXECUTION_TIME, MAX_MODEL_DISPOSE_TIME, DEFAULT_MODEL_OPTIONS } from "../../init.js";

export default () => {
  describe("HeliumForCausalLM", () => {
    const model_id = "hf-internal-testing/tiny-random-HeliumForCausalLM";
    /** @type {HeliumForCausalLM} */
    let model;
    /** @type {PreTrainedTokenizer} */
    let tokenizer;
    beforeAll(async () => {
      model = await HeliumForCausalLM.from_pretrained(model_id, DEFAULT_MODEL_OPTIONS);
      tokenizer = await PreTrainedTokenizer.from_pretrained(model_id);
      tokenizer.padding_side = "left";
    }, MAX_MODEL_LOAD_TIME);

    it(
      "batch_size=1",
      async () => {
        const inputs = tokenizer("hello");
        const outputs = await model.generate({
          ...inputs,
          max_length: 10,
        });
        expect(outputs.tolist()).toEqual([[1n, 456n, 5660n, 1700n, 1486n, 37744n, 35669n, 39396n, 12024n, 32253n]]);
      },
      MAX_TEST_EXECUTION_TIME,
    );

    it(
      "batch_size>1",
      async () => {
        const inputs = tokenizer(["hello", "hello world"], { padding: true });
        const outputs = await model.generate({
          ...inputs,
          max_length: 10,
        });
        expect(outputs.tolist()).toEqual([
          [3n, 1n, 456n, 5660n, 1700n, 1486n, 37744n, 35669n, 39396n, 12024n],
          [1n, 456n, 5660n, 998n, 6136n, 2080n, 172n, 8843n, 40579n, 23953n],
        ]);
      },
      MAX_TEST_EXECUTION_TIME,
    );

    afterAll(async () => {
      await model?.dispose();
    }, MAX_MODEL_DISPOSE_TIME);
  });
};