Update README.md

README.md

@@ -70,6 +70,27 @@ chainlit run app_pretrain.py
 
 This will launch a web application where you can input text and see the model's generated responses.
 
+### Downloading from Huggingface 🤗
+
+To interact with the model by downloading from huggingface:
+
+- First clone the repo in the local
+
+```bash
+from transformer_blocks.gpt2 import GPT2
+from gpt_Pretraining.text_generation import Text_Generation
+
+model = GPT2.from_pretrained("NamrataThakur/Small_Language_Model_MHA_53M_Pretrained")
+model.eval()
+
+#---------------------------- Checking the generation to make everything is okay ---------------------------
+generation = Text_Generation(model=model, device='cpu', tokenizer_model='gpt2', 
+                                          arch_type='original')
+start_context = "One day, a "
+response = generation.text_generation(input_text=start_context, max_new_tokens = 160, temp = 0.5, top_k=10, kv_cache=False)
+print(response)
+```
+
 ## Model Architecture and Objective
 
 Stories-SLM uses a standard GPT decoder-only transformer architecture with: