Update README.md

README.md

@@ -1,7 +1,7 @@
 ---
 license: other
 license_name: tongyi-qianwen
-license_link: https://huggingface.co/Qwen/Qwen2-beta-14B-Chat-GGUF/blob/main/LICENSE
+license_link: https://huggingface.co/Qwen/Qwen1.5-14B-Chat-GGUF/blob/main/LICENSE
 language:
 - en
 pipeline_tag: text-generation
@@ -9,12 +9,12 @@ tags:
 - chat
 ---
 
-# Qwen2-beta-14B-Chat-GGUF
+# Qwen1.5-14B-Chat-GGUF
 
 
 ## Introduction
 
-Qwen2-beta is the beta version of Qwen2, a transformer-based decoder-only language model pretrained on a large amount of data. In comparison with the previous released Qwen, the improvements include: 
+Qwen1.5 is a transformer-based decoder-only language model pretrained on a large amount of data. In comparison with the previous released Qwen, the improvements include: 
 
 * 6 model sizes, including 0.5B, 1.8B, 4B, 7B, 14B, and 72B;
 * Significant performance improvement in human preference for chat models;
@@ -26,7 +26,7 @@ For more details, please refer to our blog post and GitHub repo. In this repo, w
 <br>
 
 ## Model Details
-Qwen2 is a language model series including decoder language models of different model sizes. For each size, we release the base language model and the aligned chat model. It is based on the Transformer architecture with SwiGLU activation, attention QKV bias, group query attention, mixture of sliding window attention and full attention, etc. Additionally, we have an improved tokenizer adaptive to multiple natural languages and codes. For the beta version, temporarily we did not include GQA and the mixture of SWA and full attention.
+Qwen1.5 is a language model series including decoder language models of different model sizes. For each size, we release the base language model and the aligned chat model. It is based on the Transformer architecture with SwiGLU activation, attention QKV bias, group query attention, mixture of sliding window attention and full attention, etc. Additionally, we have an improved tokenizer adaptive to multiple natural languages and codes. For the beta version, temporarily we did not include GQA and the mixture of SWA and full attention.
 
 
 ## Training details
@@ -40,12 +40,12 @@ We advise you to clone [`llama.cpp`](https://github.com/ggerganov/llama.cpp) and
 ## How to use
 Cloning the repo may be inefficient, and thus you can manually download the GGUF file that you need or use `huggingface-cli` (`pip install huggingface_hub`) as shown below:
 ```shell
-huggingface-cli download Qwen/Qwen2-beta-14B-Chat-GGUF qwen2-beta-14b-chat-q5_k_m.gguf --local-dir . --local-dir-use-symlinks False
+huggingface-cli download Qwen/Qwen1.5-14B-Chat-GGUF qwen1_5-14b-chat-q5_k_m.gguf --local-dir . --local-dir-use-symlinks False
 ```
 
-We demonstrate how to use `llama.cpp` to run Qwen2-beta:
+We demonstrate how to use `llama.cpp` to run Qwen1.5:
 ```shell
-./main -m qwen2-beta-14b-chat-q5_k_m.gguf -n 512 --color -i -cml -f prompts/chat-with-qwen.txt
+./main -m qwen1_5-14b-chat-q5_k_m.gguf -n 512 --color -i -cml -f prompts/chat-with-qwen.txt
 ```