Update README.md

README.md

@@ -14,7 +14,7 @@ It was introduced in the paper [ColPali: Efficient Document Retrieval with Visio
 
 ## Model Description
 
-This model is trained with an extra 100k samples from the Docmatix dataset !
+This model is trained with an extra 150k samples from the Docmatix dataset !
 
 This model is built iteratively starting from an off-the-shelf [SigLIP](https://huggingface.co/google/siglip-so400m-patch14-384) model. 
 We finetuned it to create [BiSigLIP](https://huggingface.co/vidore/bisiglip) and fed the patch-embeddings output by SigLIP to an LLM, [PaliGemma-3B](https://huggingface.co/google/paligemma-3b-mix-448) to create [BiPali](https://huggingface.co/vidore/bipali). 
@@ -58,7 +58,7 @@ def main() -> None:
     """Example script to run inference with ColPali"""
 
     # Load model
-    model_name = "vidore/colpali"
+    model_name = "manu/colpali-3b-mix-448-docmatix"
     model = ColPali.from_pretrained("google/paligemma-3b-mix-448", torch_dtype=torch.bfloat16, device_map="cuda").eval()
     model.load_adapter(model_name)
     processor = AutoProcessor.from_pretrained(model_name)