Update README.md

README.md

@@ -1,11 +1,11 @@
 ---
 base_model:
 - meta-llama/Llama-3.1-8B-Instruct
-- google/siglip-so400m-patch14-384
+- google/siglip2-so400m-patch14-384
 tags:
 - captioning
 ---
-# Model Card for Llama JoyCaption Alpha Two
+# Model Card for Llama JoyCaption Beta One
 
 [Github](https://github.com/fpgaminer/joycaption)
 
@@ -103,7 +103,7 @@ with torch.no_grad():
 vLLM provides the highest performance inference for JoyCaption, and an OpenAI compatible API so JoyCaption can be used like any other VLMs.  Example usage:
 
 ```
-vllm serve fancyfeast/llama-joycaption-alpha-two-hf-llava --max-model-len 4096 --enable-prefix-caching
+vllm serve fancyfeast/llama-joycaption-beta-one-hf-llava --max-model-len 4096 --enable-prefix-caching
 ```
 
 VLMs are a bit finicky on vLLM, and vLLM is memory hungry, so you may have to adjust settings for your particular environment, such as forcing eager mode, adjusting max-model-len, adjusting gpu_memory_utilization, etc.