import transformers
import os
import torch
import requests

MAX_LEN = 150 #256
TRAIN_BATCH_SIZE = 8
VALID_BATCH_SIZE = 4
EPOCHS = 5

# Folder to contain all the datasets
# from huggingface_hub import hf_hub_download
# print("hi")
# hf_hub_download(repo_id="thak123/bert-emoji-latvian-twitter-classifier", filename="model.bin",local_dir="./")

# from huggingface_hub import snapshot_download
# snapshot_download(repo_id="thak123/bert-emoji-latvian-twitter-classifier", allow_patterns="*.bin")


# import requests
URL = "https://huggingface.co/thak123/bert-emoji-latvian-twitter-classifier/resolve/main/model.bin"
response = requests.get(URL)
open("model.bin", "wb").write(response.content)


DATASET_LOCATION = "" # 
MODEL_PATH = "model.bin"

device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

# 7 EPOCH Version
BERT_PATH = "FFZG-cleopatra/bert-emoji-latvian-twitter"


# TODO check if lower casing is required
# BertTokenizer
TOKENIZER = transformers.BertTokenizer.from_pretrained(
    BERT_PATH,
    do_lower_case=True
)

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