Update README.md

README.md

@@ -48,7 +48,7 @@ Below we share some code snippets on how to get quickly started with running the
 
 #### Fine-tuning the model
 
-You can find fine-tuning scripts and notebook under the [`examples/` directory](https://huggingface.co/google/gemma-7b/tree/main/examples) of [`google/gemma-7b`](https://huggingface.co/google/gemma-7b) repository. To adapt it to this model, simply change the model-id to `google/gemma-7b-it`.
+You can find fine-tuning scripts and notebook under the [`examples/` directory](https://huggingface.co/google/gemma-7b/tree/main/examples) of [`google/gemma-7b`](https://huggingface.co/google/gemma-7b) repository. To adapt it to this model, simply change the model-id to `yatharth97/yatharth-gemma-7b-it-10k`.
 In that repository, we provide:
 
 * A script to perform Supervised Fine-Tuning (SFT) on UltraChat dataset using QLoRA
@@ -229,7 +229,7 @@ from transformers import AutoTokenizer, AutoModelForCausalLM
 import transformers
 import torch
 
-model_id = "google/gemma-7b-it"
+model_id = "yatharth97/yatharth-gemma-7b-it-10k"
 dtype = torch.bfloat16
 
 tokenizer = AutoTokenizer.from_pretrained(model_id)