Update README.md

README.md

@@ -1,3 +1,58 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+datasets:
+- mozilla-foundation/common_voice_17_0
+language:
+- uz
+metrics:
+- wer
+base_model: facebook/wav2vec2-base-960h
+pipeline_tag: automatic-speech-recognition
+library_name: adapter-transformers
+---
+
+# Author
+
+ Mamayusupov Rifat.
+
+# Usage
+
+```
+from transformers import SeamlessM4TFeatureExtractor, Wav2Vec2BertProcessor, Wav2Vec2CTCTokenizer, Wav2Vec2BertForCTC
+from transformers import pipeline
+
+# Initialize tokenizer
+tokenizer = Wav2Vec2CTCTokenizer.from_pretrained("/home/rifat/asr", unk_token="[UNK]", pad_token="[PAD]", word_delimiter_token="|")
+
+# Initialize feature extractor
+feature_extractor = SeamlessM4TFeatureExtractor(feature_size=80, num_mel_bins=80, sampling_rate=16000, padding_value=0.0)
+
+# Initialize processor
+processor = Wav2Vec2BertProcessor(feature_extractor=feature_extractor, tokenizer=tokenizer)
+
+# Initialize model
+model = Wav2Vec2BertForCTC.from_pretrained(
+    args.pretrained_model,
+    attention_dropout=0.0,
+    hidden_dropout=0.0,
+    feat_proj_dropout=0.0,
+    mask_time_prob=0.0,
+    layerdrop=0.0,
+    ctc_loss_reduction="mean",
+    add_adapter=True,
+    pad_token_id=processor.tokenizer.pad_token_id,
+    vocab_size=len(processor.tokenizer),
+    ignore_mismatched_sizes=True
+)
+
+model.config.ctc_zero_infinity = True
+model.to("cuda")
+
+# Perform inference
+# Initialize the pipeline
+pipe = pipeline(model=model, tokenizer=processor.tokenizer, feature_extractor=feature_extractor, task="automatic-speech-recognition")
+
+input_audio = ""
+print(pipe(input_audio)['result_text'])
+
+```