Update README.md

README.md

@@ -35,7 +35,7 @@ The model is designed for developers and software teams to automatically generat
 
 ## Dataset
 
-### Dataset: `princeton-nlp/SWE-bench_Lite`
+### `princeton-nlp/SWE-bench_Lite`
 
 This model is fine-tuned on the `swe_bench` dataset. The dataset includes:
 - **<issue> (Issue Description)**: Describes the bug in detail.
@@ -56,8 +56,8 @@ This model is fine-tuned on the `swe_bench` dataset. The dataset includes:
 from transformers import LlamaForCausalLM, LlamaTokenizer
 
 # Load the model and tokenizer
-model = LlamaForCausalLM.from_pretrained('gtandon/ft_llama3_1_swe_bench')
-tokenizer = LlamaTokenizer.from_pretrained('gtandon/ft_llama3_1_swe_bench')
+model = LlamaForCausalLM.from_pretrained('anant58/swe-model')
+tokenizer = LlamaTokenizer.from_pretrained('anant58/swe-model')
 
 # Example input (issue description)
 issue_description = "Function X throws an error when Y happens."