You can set the batch size as follows (it’s in the updated course-v3)
bs =24
data_lm = TextLMDataBunch.load(path, 'tmp_lm', bs=bs)
You can specify the settings of max_vocab and the language as follows.
txt_proc = [
TokenizeProcessor(tokenizer=Tokenizer(lang='nl') ),
NumericalizeProcessor(min_freq=1, max_vocab=10000 )
]
data_lm = (TextList.from_df(df, cols='text', processor=txt_proc)
.random_split_by_pct(0.1)
.label_for_lm()
.databunch())