Upload 7 files

config.json

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+{
+  "_name_or_path": "../models/checkpoint-51000",
+  "architectures": [
+    "T5ForConditionalGeneration"
+  ],
+  "d_ff": 2048,
+  "d_kv": 64,
+  "d_model": 768,
+  "decoder_start_token_id": 0,
+  "dense_act_fn": "gelu_new",
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "gated-gelu",
+  "gradient_checkpointing": false,
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "is_gated_act": true,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "t5",
+  "num_decoder_layers": 12,
+  "num_heads": 12,
+  "num_layers": 12,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.26.1",
+  "use_cache": true,
+  "vocab_size": 32128
+}

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b8838cfea72e70c11e9a671798b8490e57f4cf509b7efbf4691aca57e0924f86
+size 990406605

readme.md

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+---
+language: 
+  - zh
+license: apache-2.0
+tags:
+- t5
+- text error correction
+widget:
+- text: "今天天气不太好，我的心情也不是很偷快"
+  example_title: "案例1"
+- text: "能不能帮我买点淇淋，好久没吃了。"
+  example_title: "案例2"
+- text: "脑子有点胡涂了，这道题冥冥学过还没有做出来"
+  example_title: "案例3"
+inference:
+  parameters:
+    max_length: 256
+    num_beams: 10
+    no_repeat_ngram_size: 5
+    do_sample: True
+    early_stopping: True
+​---
+
+---
+
+## 功能介绍
+
+T5Corrector：中文字音与字形纠错模型
+
+这个模型是基于mengzi-t5-base进行文本纠错训练，使用2kw+句子，通过替换同音词、近音词和形近字来，对于句中词组随机添加词组、删除词组中的部分字，以及字词乱序操作构造纠错平行语料，共计2亿+句对，累计训练66000步。
+
+<a href='https://github.com/Macielyoung/T5Corrector'>Github项目地址</a>
+
+
+
+加载模型：
+
+ ```python
+# 加载模型
+from transformers import T5Tokenizer, T5ForConditionalGeneration
+pretrained = "Maciel/T5Corrector-base-v2"
+tokenizer = T5Tokenizer.from_pretrained(pretrained)
+model = T5ForConditionalGeneration.from_pretrained(pretrained)
+ ```
+
+使用模型进行预测推理方法：
+```python
+import torch
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+
+def correct(text, max_length):
+		model_inputs = tokenizer(text, 
+                           	 max_length=max_length, 
+                           	 truncation=True, 
+                           	 return_tensors="pt").to(device)
+    output = model.generate(**model_inputs, 
+                              num_beams=5,
+                              no_repeat_ngram_size=4,
+                              do_sample=True, 
+                              early_stopping=True,
+                              max_length=max_length,
+                              return_dict_in_generate=True,
+                              output_scores=True)
+    pred_output = tokenizer.batch_decode(output.sequences, skip_special_tokens=True)[0]
+    return pred_output
+
+text = "贵州毛台现在多少钱一瓶啊，想买两瓶尝尝味道。"
+correction = correct(text, max_length=32)
+print(correction)
+```
+
+
+
+### 案例展示
+
+```
+示例1:
+input: 能不能帮我买点淇淋，好久没吃了。
+output: 能不能帮我买点冰淇淋，好久没吃了。
+
+示例2:
+input: 脑子有点胡涂了，这道题冥冥学过还没有做出来
+output: 脑子有点糊涂了,这道题明明学过还没有做出来
+
+示例3:
+input: 今天天气不太好，我的心情也不是很偷快
+output: 今天天气不太好,我的心情也不是很愉快
+```

rng_state.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:79eca5b7bc5e5e2d1c93652e949356c232eb8cce4abc67830051c0e1d950638a
+size 15523

special_tokens_map.json

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+  "eos_token": "</s>",
+  "pad_token": "<pad>",
+  "unk_token": "<unk>"
+}

tokenizer_config.json

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+{
+  "additional_special_tokens": [
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+}