decode(ids, skip_special_tokens=True) # 'this is a apple' slow_tokenizer = T5Tokenizer.from_pretrained(path) num = slow_tokenizer.add_tokens(["ஐ"], special_tokens=True) assert num == 1 ids = slow_tokenizer(text)["input_ids"] slow_tokenizer.decode(ids, skip_special_tokens=True) ...
inputs = tokenizer(text, return_tensors="pt").to(device) outputs = model.generate(**inputs, max_new_tokens=20) print(tokenizer.decode(outputs[0], skip_special_tokens=True)) 模型完成了一个合理的补全,尽管有一些额外的 token: Quote:Imaginationismore important than knowledge. Knowledgeislimited....
# 将字符串转换为id序列,又称之为编码 ids = tokenizer.encode(sen, add_special_tokens=True) ids 编码的结果 #将id序列转换为字符串,又称之为解码 str_sen = tokenizer.decode(ids, skip_special_tokens=False) str_sen 解码的结果 Step5 填充与截断 # 填充 ids = tokenizer.encode(sen, padding="max_...
answer_end_index = outputs.end_logits.argmax() predict_answer_tokens = inputs.input_ids[0, answer_start_index : answer_end_index + 1] tokenizer.decode(predict_answer_tokens, skip_special_tokens=True) 'a nice puppet' 比较好理解,推理的时候从原答案中找出start和end编号就行。 3:BertForToken...
print(tokenizer.decode(outputs[0], skip_special_tokens=True)) Output: --- Wie alt bist du? 使用约束波束搜索 但是如果我们想要一个正式的表达而不是非正式的表达呢?如果我们已经先验地知道输出中必须包含什么,我们该如何将其注入到输出中呢? 我们可以...
You could add skip_special_tokens=True to the generation_kwargs. Alternatively you could check every generated token id against the tokenizers list of special tokens and filter accordingly. Share Improve this answer Follow answered Jan 9 at 14:31 zhksh 2133 bronze badges Add a comment Your...
这是huggingface设计的一种新格式,大致就是以更加紧凑、跨框架的方式存储Dict[str, Tensor],主要存储的...
_text = tokenizer.decode(torch.argmax(ids, dim=-1), skip_special_tokens=True).replace(' ', '') corrected_text = _text[:len(text)] corrected_text = get_errors(corrected_text, text) result.append(corrected_text) result.append('\n') ...
decoded_summaries = [tokenizer.decode(s, skip_special_tokens=True, clean_up_tokenization_spaces=True) for s in summaries] decoded_summaries = [d.replace("<n>", " ") for d in decoded_summaries] metric.add_batch(predictions=decoded_summaries, references=target_batch) ...
re = tokenizer.decode(model.generate(**ipt,max_length=256,do_sample=False)[0],skip_special_tokens=True) print(re) 最终返回 登陆后复制1 2 3 4 5 6 7 8 9 10 11 12 13 登陆后复制Assistant:1.在BIOS中,选择“Advanced BIOS Features”;2.在“Advanced Features”中,选择“System Configuration”...