Update README.md

README.md

@@ -1,11 +1,11 @@
 ---
 library_name: transformers
 license: apache-2.0
-license_link: https://huggingface.co/huihui-ai/Qwen2.5-Code-7B-Instruct-abliterated/blob/main/LICENSE
+license_link: https://huggingface.co/huihui-ai/Qwen2.5-Coder-7B-Instruct-abliterated/blob/main/LICENSE
 language:
 - en
 pipeline_tag: text-generation
-base_model: Qwen/Qwen2.5-Code-7B-Instruct
+base_model: Qwen/Qwen2.5-Coder-7B-Instruct
 tags:
 - chat
 - abliterated
@@ -15,7 +15,7 @@ tags:
 # huihui-ai/Qwen2.5-Code-1.5B-Instruct-abliterated
 
 
-This is an uncensored version of [Qwen2.5-Code-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Code-7B-Instruct) created with abliteration (see [this article](https://huggingface.co/blog/mlabonne/abliteration) to know more about it).
+This is an uncensored version of [Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct) created with abliteration (see [this article](https://huggingface.co/blog/mlabonne/abliteration) to know more about it).
 
 Special thanks to [@FailSpy](https://huggingface.co/failspy) for the original code and technique. Please follow him if you're interested in abliterated models.
 
@@ -27,7 +27,7 @@ You can use this model in your applications by loading it with Hugging Face's `t
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 # Load the model and tokenizer
-model_name = "huihui-ai/Qwen2.5-Code-7B-Instruct-abliterated"
+model_name = "huihui-ai/Qwen2.5-Coder-7B-Instruct-abliterated"
 model = AutoModelForCausalLM.from_pretrained(
     model_name,
     torch_dtype="auto",