94 lines
2.4 KiB
JavaScript
94 lines
2.4 KiB
JavaScript
//load Candle Bert Module wasm module
|
|
let init, ModelConditionalGeneration;
|
|
|
|
async function fetchArrayBuffer(url) {
|
|
const cacheName = "t5-candle-cache";
|
|
const cache = await caches.open(cacheName);
|
|
const cachedResponse = await cache.match(url);
|
|
if (cachedResponse) {
|
|
const data = await cachedResponse.arrayBuffer();
|
|
return new Uint8Array(data);
|
|
}
|
|
const res = await fetch(url, { cache: "force-cache" });
|
|
cache.put(url, res.clone());
|
|
return new Uint8Array(await res.arrayBuffer());
|
|
}
|
|
class ConditionalGeneration {
|
|
static instance = {};
|
|
|
|
static async getInstance(weightsURL, tokenizerURL, configURL, modelID) {
|
|
if (modelID.includes("quantized")) {
|
|
({ default: init, ModelConditionalGeneration } = await import(
|
|
"./build/m-quantized.js"
|
|
));
|
|
} else {
|
|
({ default: init, ModelConditionalGeneration } = await import(
|
|
"./build/m.js"
|
|
));
|
|
}
|
|
if (!this.instance[modelID]) {
|
|
await init();
|
|
|
|
self.postMessage({ status: "loading", message: "Loading Model" });
|
|
const [weightsArrayU8, tokenizerArrayU8, configArrayU8] =
|
|
await Promise.all([
|
|
fetchArrayBuffer(weightsURL),
|
|
fetchArrayBuffer(tokenizerURL),
|
|
fetchArrayBuffer(configURL),
|
|
]);
|
|
|
|
this.instance[modelID] = new ModelConditionalGeneration(
|
|
weightsArrayU8,
|
|
tokenizerArrayU8,
|
|
configArrayU8
|
|
);
|
|
} else {
|
|
self.postMessage({ status: "ready", message: "Model Already Loaded" });
|
|
}
|
|
return this.instance[modelID];
|
|
}
|
|
}
|
|
|
|
self.addEventListener("message", async (event) => {
|
|
const { weightsURL, tokenizerURL, configURL, modelID, prompt, params } =
|
|
event.data;
|
|
let {
|
|
temperature = 0.0,
|
|
seed = 299792458,
|
|
repeat_penalty = 1.1,
|
|
repeat_last_n = 64,
|
|
top_p = 1,
|
|
} = { ...params };
|
|
try {
|
|
self.postMessage({
|
|
status: "ready",
|
|
message: "Starting T5 Conditional Generation",
|
|
});
|
|
const model = await ConditionalGeneration.getInstance(
|
|
weightsURL,
|
|
tokenizerURL,
|
|
configURL,
|
|
modelID
|
|
);
|
|
self.postMessage({
|
|
status: "decoding",
|
|
message: "Decoding Prompt",
|
|
});
|
|
const output = model.decode({
|
|
prompt,
|
|
temperature,
|
|
seed,
|
|
top_p,
|
|
repeat_penalty,
|
|
repeat_last_n,
|
|
});
|
|
self.postMessage({
|
|
status: "complete",
|
|
message: "complete",
|
|
output: output,
|
|
});
|
|
} catch (e) {
|
|
self.postMessage({ error: e });
|
|
}
|
|
});
|