Create create_model.py

create_model.py

@@ -0,0 +1,27 @@
+from transformers import SpeechEncoderDecoderModel, AutoFeatureExtractor, AutoTokenizer
+import torch
+
+
+encoder_id = "facebook/wav2vec2-xls-r-300m"
+decoder_id = "facebook/bart-base"
+
+model = SpeechEncoderDecoderModel.from_encoder_decoder_pretrained(encoder_id, decoder_id, encoder_add_adapter=True)
+model.config.encoder.feat_proj_dropout = 0.0
+model.config.encoder.mask_time_prob = 0.0
+model.config.decoder_start_token_id = model.decoder.config.bos_token_id
+model.config.pad_token_id = model.decoder.config.pad_token_id
+model.config.eos_token_id = model.decoder.config.eos_token_id
+model.config.max_length = 40
+model.config.encoder.layerdrop = 0.0
+model.config.use_cache = False
+model.config.processor_class = "Wav2Vec2Processor"
+
+# check if generation works
+out = model.generate(torch.ones((1, 2000)))
+
+model.save_pretrained("./")
+
+feature_etxractor = AutoFeatureExtractor.from_pretrained(encoder_id)
+feature_etxractor.save_pretrained("./")
+tokenizer = AutoTokenizer.from_pretrained(decoder_id)
+tokenizer.save_pretrained("./")