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import { BloomTokenizer, BloomForCausalLM } 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("BloomForCausalLM", () => {
const model_id = "hf-internal-testing/tiny-random-BloomForCausalLM";
/** @type {BloomForCausalLM} */
let model;
/** @type {BloomTokenizer} */
let tokenizer;
beforeAll(async () => {
model = await BloomForCausalLM.from_pretrained(model_id, DEFAULT_MODEL_OPTIONS);
tokenizer = await BloomTokenizer.from_pretrained(model_id);
}, 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([[198n, 803n, 82n, 82n, 82n, 82n, 82n, 82n, 82n, 82n]]);
},
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, 3n, 198n, 803n, 82n, 82n, 82n, 82n, 82n, 82n],
[198n, 803n, 82n, 209n, 753n, 753n, 753n, 753n, 753n, 753n],
]);
},
MAX_TEST_EXECUTION_TIME,
);
afterAll(async () => {
await model?.dispose();
}, MAX_MODEL_DISPOSE_TIME);
});
};
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