tokenizer.encode_plus(s, max_length=lim, truncation=True, padding='max_length', return_tensors='pt') def __len__(self): return self.df.shape[0] def __getitem__(self, idx): x = self.encode_str(self.df.loc[idx, self.xcol], self.xmax) y = self.encode_str(self.df.loc[idx,...
layer=None, heads=None): inputs = tokenizer.encode_plus(sentence_a, sentence_b, return_ten...
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此demo可以通过拖拽左边栏的项目,自己设计一个单选、多选或有下拉菜单的题目,通过Vue实现关联. Contribute to HaHaHong/Self-created-problem-form development by creating an account on GitHub.
query = "cardiopathy" query_toks = tokenizer.batch_encode_plus([query], padding="max_length", max_length=25, truncation=True, return_tensors="pt") print(query_toks) query_output = model(**query_toks) query_cls_rep = query_output[0][:,0,:] ...
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arange(0, len(all_names), bs)): toks = tokenizer.batch_encode_plus(all_names[i:i+bs], padding="max_length", max_length=25, truncation=True, return_tensors="pt") toks_cuda = {} for k,v in toks.items(): toks_cuda[k] = v.cuda() cls_rep = model(**toks_cuda)[0][:...
> # processing instruction ) """, re.X) def _escape_special_chars(self, text): # Python markdown note: the HTML tokenization here differs from # that in Markdown.pl, hence the behaviour for subtle cases can # differ (I believe the tokenizer here does a better job because # it isn...
此demo可以通过拖拽左边栏的项目,自己设计一个单选、多选或有下拉菜单的题目,通过Vue实现关联. Contribute to Rekoe/Self-created-problem-form development by creating an account on GitHub.