openbmb
/

MiniCPM-Embedding-Light

Feature Extraction

sentence-transformers

Eval Results (legacy)

Model card Files Files and versions

Kaguya-19 commited on Jan 21, 2025

Commit

1d0117a

·

verified ·

1 Parent(s): 5643d0d

Update scripts/test_mteb.py

Files changed (1) hide show

scripts/test_mteb.py +1 -1

scripts/test_mteb.py CHANGED Viewed

@@ -352,7 +352,7 @@ class DenseEncoder(torch.nn.Module):
     def __init__(self, **kwargs):
         super().__init__()
-        model_path = "openbmb/UltraRAG-Embedding"
         self.encoder = AutoModel.from_pretrained(model_path, trust_remote_code=True,attn_implementation="flash_attention_2", torch_dtype=torch.float16).to("cuda")
         self.tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
         self.gpu_count = torch.cuda.device_count()

     def __init__(self, **kwargs):
         super().__init__()
+        model_path = "openbmb/MiniCPM-Embedding-Light"
         self.encoder = AutoModel.from_pretrained(model_path, trust_remote_code=True,attn_implementation="flash_attention_2", torch_dtype=torch.float16).to("cuda")
         self.tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
         self.gpu_count = torch.cuda.device_count()