Update README.md

README.md

@@ -332,7 +332,7 @@ Then you can load this model and run inference.
 from sentence_transformers import SentenceTransformer
 
 # Download from the 🤗 Hub
-model = SentenceTransformer("JacobLinCool/Qwen3-Embedding-GIR-1")
+model = SentenceTransformer("JacobLinCool/Qwen3-Embedding-8B-GIR-1")
 # Run inference
 queries = [
     "Generates samples of text from the provided vocabulary.\n\n  Args:\n    plain_vocab: vocabulary.\n    distribution: distribution.\n    train_samples: samples for training.\n    length: length.\n\n  Returns:\n    train_indices (np.array of Integers): random integers for training.\n      shape = [num_samples, length]\n    test_indices (np.array of Integers): random integers for testing.\n      shape = [num_samples, length]\n    plain_vocab   (list of Integers): unique vocabularies.",
@@ -488,7 +488,7 @@ You can finetune this model on your own dataset.
 - `load_best_model_at_end`: True
 - `optim`: paged_adamw_8bit
 - `push_to_hub`: True
-- `hub_model_id`: JacobLinCool/Qwen3-Embedding-GIR-1
+- `hub_model_id`: JacobLinCool/Qwen3-Embedding-8B-GIR-1
 - `hub_private_repo`: False
 - `gradient_checkpointing`: True
 - `eval_on_start`: True
@@ -578,7 +578,7 @@ You can finetune this model on your own dataset.
 - `use_legacy_prediction_loop`: False
 - `push_to_hub`: True
 - `resume_from_checkpoint`: None
-- `hub_model_id`: JacobLinCool/Qwen3-Embedding-GIR-1
+- `hub_model_id`: JacobLinCool/Qwen3-Embedding-8B-GIR-1
 - `hub_strategy`: every_save
 - `hub_private_repo`: False
 - `hub_always_push`: False