create

README.md

@@ -1,3 +1,25 @@
+---
+language: zh
+---
+
+## bert-chinese-large-homie
+
+This is a Chinese pre-training model BERT, pre-trained on a large-scale corpus. It is suitable for fine-tuning on specific downstream tasks, or as a parameter initialization for pre-training, which can improve performance. Due to excessive alchemy, it is not suitable for Fill Mask directly, unless you have performed a small amount of pre-training.
+
+I don't know what homie means, but someone calls me that. I believe this is an interesting natural language processing. I don't know what homie means, but I've been called that and I can feel the meaning. 
+
+## Bibtex entry and citation info
+Please cite if you find it helpful.
+```
+@article{zhu2023metaaid,
+  title={MetaAID 2.0: An Extensible Framework for Developing Metaverse Applications via Human-controllable Pre-trained Models},
+  author={Zhu, Hongyin},
+  journal={arXiv preprint arXiv:2302.13173},
+  year={2023}
+}
+
+```
+
 ---
 license: other
 ---

added_tokens.json

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config.json

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+{
+  "_name_or_path": "yechen/bert-large-chinese",
+  "architectures": [
+    "BertForMaskedLM"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "pooler_fc_size": 768,
+  "pooler_num_attention_heads": 12,
+  "pooler_num_fc_layers": 3,
+  "pooler_size_per_head": 128,
+  "pooler_type": "first_token_transform",
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.27.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 21139
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "pad_token_id": 0,
+  "transformers_version": "4.27.1"
+}

pytorch_model.bin

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special_tokens_map.json

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+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
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+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
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+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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