Create README.md

README.md

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+##Created from ted-multi dataset
+
+adding processing steps here if you want another language
+
+#using Turkish as target
+target_lang="tr"  # change to your target lang
+
+
+from datasets import load_dataset
+#ted-multi is a multiple language translated dataset
+#fits for our case , not to big and curated
+
+dataset = load_dataset("ted_multi")
+
+#there is no Turkish lanugage in europarl, so will need to choose one
+dataset.cleanup_cache_files()
+
+
+#chars_to_ignore_regex = '[,?.!\-\;\:\"“%‘”�—’…–]'  # change to the ignored characters of your fine-tuned model
+
+#will use cahya/wav2vec2-base-turkish-artificial-cv
+#checking inside model repository to find which chars removed (no run.sh)
+chars_to_ignore_regex = '[\,\?\.\!\-\;\:\"\“\‘\”\'\`…\’»«]'
+
+cols_to_remove =  ['translations', 'talk_name']
+dataset = dataset.map(extract_target_lang_entries, remove_columns=cols_to_remove)
+
+
+dataset_cleaned = dataset.filter(lambda x: x['text'] is not None)
+dataset_cleaned
+
+from huggingface_hub import notebook_login
+
+notebook_login()
+
+dataset_cleaned.push_to_hub(f"{target_lang}_ted_talk_translated")