Update README.md

README.md

@@ -7,22 +7,12 @@ Overview: This model is fine-tuned for text normalization in Hindi. It converts
 
 Training Details
 Model Architecture: T5-small
+
 Dataset: An augmented version of SPRINGLab/IndicVoices-R_Hindi, further enriched with synthetic examples for dates, currencies, and units.
+
 Hyperparameters:
 Learning rate: 2e-5
 Epochs: 3
 Per-device batch size: 2 (with gradient accumulation)
 FP16 enabled for mixed precision training
-Environment: Trained on Google Colab with a GPU.
-
-
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-
-# Load model and tokenizer from Hugging Face Hub
-tokenizer = AutoTokenizer.from_pretrained("shubham-Bgs/Text-normalization-hindi")
-model = AutoModelForSeq2SeqLM.from_pretrained("shubham-Bgs/Text-normalization-hindi")
-
-input_text = "15 / 03 / 1990 को, वैज्ञानिक ने $120 में 500 mg का नमूना खरीदा।"
-inputs = tokenizer(input_text, return_tensors="pt", padding=True)
-outputs = model.generate(**inputs)
-print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+Environment: Trained on Google Colab with a GPU.