juanluisdb
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MiniLM-L-6-rerank-m3

Text Classification

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juanluisdb commited on Sep 26

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@@ -24,7 +24,7 @@ using [bge-reranker-v2-m3](https://huggingface.co/BAAI/bge-reranker-v2-m3) as te
 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch
-model = AutoModelForSequenceClassification.from_pretrained("juanluisdb/MiniLM-L-6-rerank-reborn")
 tokenizer = AutoTokenizer.from_pretrained("juanluisdb/MiniLM-L-6-rerank-m3")
 features = tokenizer(['How many people live in Berlin?', 'How many people live in Berlin?'], ['Berlin has a population of 3,520,031 registered inhabitants in an area of 891.82 square kilometers.', 'New York City is famous for the Metropolitan Museum of Art.'],  padding=True, truncation=True, return_tensors="pt")
 model.eval()

 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch
+model = AutoModelForSequenceClassification.from_pretrained("juanluisdb/MiniLM-L-6-rerank-m3")
 tokenizer = AutoTokenizer.from_pretrained("juanluisdb/MiniLM-L-6-rerank-m3")
 features = tokenizer(['How many people live in Berlin?', 'How many people live in Berlin?'], ['Berlin has a population of 3,520,031 registered inhabitants in an area of 891.82 square kilometers.', 'New York City is famous for the Metropolitan Museum of Art.'],  padding=True, truncation=True, return_tensors="pt")
 model.eval()