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README.md

@@ -22,7 +22,7 @@ datasets:
 - ms_marco
 ---
 
-# Liner/embeddinggemma-300m-academic for Academic Search
+# LinerAI/embeddinggemma-300m-academic for Academic Search
 
 This is a fine-tuned version of [google/gemma-3-300m](https://huggingface.co/google/gemma-3-300m) optimized for **academic and scientific literature search**. The model has been trained using contrastive learning with hard negative mining, specifically curated for academic search scenarios.
 
@@ -96,7 +96,7 @@ embedding_128 = embeddings[:, :128]
 import torch
 from transformers import AutoModel, AutoTokenizer
 
-model_path = "Liner/embeddinggemma-300m-academic"
+model_path = "LinerAI/embeddinggemma-300m-academic"
 tokenizer = AutoTokenizer.from_pretrained(model_path)
 model = AutoModel.from_pretrained(model_path, torch_dtype=torch.bfloat16)
 model.eval()