Update README.md

README.md

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-# Merged_Aura_Airavata
-
-This model merges **Aura_v3_7B** and **Airavata** using upscaling and weighted blending.
-
-## Model Details
-- **Base Models:** `ResplendentAI/Aura_v3_7B` + `ai4bharat/Airavata`
-- **Merging Method:** Upscaling + Weighted Averaging (α=0.5)
-- **Tokenizer:** Compatible with `Llama` tokenizers
-
-## Usage
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-model = AutoModelForCausalLM.from_pretrained("YOUR_USERNAME/Merged_Aura_Airavata")
-tokenizer = AutoTokenizer.from_pretrained("YOUR_USERNAME/Merged_Aura_Airavata")
-
-prompt = "Hello, how are you?"
-input_ids = tokenizer(prompt, return_tensors="pt").input_ids
-output = model.generate(input_ids)
-print(tokenizer.decode(output[0], skip_special_tokens=True))
+# Merged_Aura_Airavata
+
+This model merges **Aura_v3_7B** and **Airavata** using upscaling and weighted blending.
+
+## Model Details
+- **Base Models:** `ResplendentAI/Aura_v3_7B` + `ai4bharat/Airavata`
+- **Merging Method:** Upscaling + Weighted Averaging (α=0.5)
+- **Tokenizer:** Compatible with `Llama` tokenizers
+
+## Usage
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("Divyansh008/Merged_Aura_Airavata")
+tokenizer = AutoTokenizer.from_pretrained("Divyansh008/Merged_Aura_Airavata")
+
+prompt = "Hello, how are you?."
+input_ids = tokenizer(prompt, return_tensors="pt").input_ids
+output = model.generate(input_ids)
+print(tokenizer.decode(output[0], skip_special_tokens=True))