arazd
/

MIReAD

Text Classification

representations

scientific documents

text-embeddings-inference

Model card Files Files and versions

arazd commited on May 7, 2023

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cee7259

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1 Parent(s): ef0c027

Update README.md

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@@ -33,10 +33,12 @@ tokenizer = AutoTokenizer.from_pretrained(mpath)
 To use MIReAD for feature extraction and classification:
 ```python
-# sample abstract text
 abstr = 'Learning semantically meaningful representations from scientific documents can ...'
 source_len = 512
-inputs = tokenizer(abstr,
                    max_length = source_len,
                    pad_to_max_length=True,
                    truncation=True,

 To use MIReAD for feature extraction and classification:
 ```python
+# sample abstract & title text
+title = 'MIReAD: simple method for learning scientific representations'
 abstr = 'Learning semantically meaningful representations from scientific documents can ...'
+text = title + tokenizer.sep_token + abstr
 source_len = 512
+inputs = tokenizer(text,
                    max_length = source_len,
                    pad_to_max_length=True,
                    truncation=True,