zhanwenchen

import os
import tensorflow as tf

trained_checkpoint_prefix = 'checkpoints/dev'
export_dir = os.path.join('models', '0') # IMPORTANT: each model folder must be named '0', '1', ... Otherwise it will fail!

loaded_graph = tf.Graph()
with tf.Session(graph=loaded_graph) as sess:
    # Restore from checkpoint
    loader = tf.train.import_meta_graph(trained_checkpoint_prefix + '.meta')

AlexV525

///
/// [Author] Alex (https://github.com/AlexV525)
/// [Date] 07/30/21 5:29 PM
///
import 'dart:typed_data';
import 'dart:ui' as ui;

import 'package:flutter/rendering.dart';
import 'package:flutter/widgets.dart';

rogeriochaves

"""You help triaging user requests. Given a raw text input, output either DOCS or DEFAULT, according to those definitions:

DOCS: if user is asking a seemingly technical question, programming questions or company-specific questions
DEFAULT: if user is just chit-chatting or basic knowledge questions

====================

Input: hello there
Output: DEFAULT

kouroshHakha

import datasets
import re
import json
import tqdm

ds = datasets.load_dataset("glaiveai/glaive-function-calling-v2", split="train")

out_ds_size = 100

class UserAssistantNotFoundError(Exception):