Update README.md

README.md

@@ -4,30 +4,30 @@ library_name: peft
 ---
 
 ## Config
+```python
+model_name_or_path = "openai/whisper-large-v2"
+language = "Marathi"
+language_abbr = "mr"
+task = "transcribe"
+dataset_name = "mozilla-foundation/common_voice_11_0"
 
-  model_name_or_path = "openai/whisper-large-v2"
-  language = "Marathi"
-  language_abbr = "mr"
-  task = "transcribe"
-  dataset_name = "mozilla-foundation/common_voice_11_0"
-  
-  feature_extractor = AutoFeatureExtractor.from_pretrained(model_name_or_path)
-  tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, language=language, task=task)
-  processor = AutoProcessor.from_pretrained(model_name_or_path, language=language, task=task)
-  
-  
-  common_voice["train"] = load_dataset(dataset_name, language_abbr, split="train+validation", use_auth_token=True)
-  common_voice["test"] = load_dataset(dataset_name, language_abbr, split="test", use_auth_token=True)
-  
-  
-  model = AutoModelForSpeechSeq2Seq.from_pretrained(model_name_or_path, load_in_8bit=True, device_map="auto")
-  config = LoraConfig(r=32, lora_alpha=64, target_modules=["q_proj", "v_proj"], lora_dropout=0.05, bias="none")
-  
-  model = get_peft_model(model, config)
-  model.print_trainable_parameters()
-  #"trainable params: 15728640 || all params: 1559033600 || trainable%: 1.0088711365810203"
+feature_extractor = AutoFeatureExtractor.from_pretrained(model_name_or_path)
+tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, language=language, task=task)
+processor = AutoProcessor.from_pretrained(model_name_or_path, language=language, task=task)
 
 
+common_voice["train"] = load_dataset(dataset_name, language_abbr, split="train+validation", use_auth_token=True)
+common_voice["test"] = load_dataset(dataset_name, language_abbr, split="test", use_auth_token=True)
+
+
+model = AutoModelForSpeechSeq2Seq.from_pretrained(model_name_or_path, load_in_8bit=True, device_map="auto")
+config = LoraConfig(r=32, lora_alpha=64, target_modules=["q_proj", "v_proj"], lora_dropout=0.05, bias="none")
+
+model = get_peft_model(model, config)
+model.print_trainable_parameters()
+#"trainable params: 15728640 || all params: 1559033600 || trainable%: 1.0088711365810203"
+```
+
 ## Training procedure