xpmir
/

cross-encoder-ettin-17m-DistillRankNET

Text Classification

sequence-classification

text-embeddings-inference

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VictorMorand commited on 1 day ago

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@@ -48,7 +48,7 @@ Quick Start:
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch
-tokenizer = AutoTokenizer.from_pretrained("jhu-clsp/ettin-encoder-17m")
 model = AutoModelForSequenceClassification.from_pretrained("xpmir/cross-encoder-ettin-17m-DistillRankNET")
 features = tokenizer("What is experimaestro ?", "Experimaestro is a powerful framework for ML experiments management...", padding=True, truncation=True, return_tensors="pt")

 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch
+tokenizer = AutoTokenizer.from_pretrained("xpmir/cross-encoder-ettin-17m-DistillRankNET")
 model = AutoModelForSequenceClassification.from_pretrained("xpmir/cross-encoder-ettin-17m-DistillRankNET")
 features = tokenizer("What is experimaestro ?", "Experimaestro is a powerful framework for ML experiments management...", padding=True, truncation=True, return_tensors="pt")