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Model: QwenCollection/RA-IT-NER-zh-7B Source: Original Platform
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README.md
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README.md
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---
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license: cc-by-nc-4.0
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language:
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- zh
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---
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---
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# RA-IT-NER-zh-7B
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**Description**: The RA-IT-NER-zh-7B model is trained from Qwen1.5-7B using the proposed Retrieval Augmented Instruction Tuning (RA-IT) approach. This model can be used for Chinese Open NER with and without RAG. The training data is our constructed [Sky-NER ](https://huggingface.co/datasets/EmmaStrong/Sky-NER), an instruction tuning dataset for Chinese OpenNER. We follow the recipe of [UniversalNER](https://arxiv.org/abs/2308.03279) and use the large-scale [SkyPile Corpus](https://huggingface.co/datasets/Skywork/SkyPile-150B) to construct this dataset. The data was collected by prompting gpt-3.5-turbo-0125 to label entities from passages and provide entity tags. The data collection prompt is as follows:
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<div style="background-color: #f6f8fa; padding: 20px; border-radius: 10px; border: 1px solid #e1e4e8; box-shadow: 0 2px 5px rgba(0,0,0,0.1);">
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<strong>Instruction:</strong><br/>
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给定一段文本，你的任务是抽取所有实体并识别它们的实体类别。输出应为以下JSON格式：[{"实体1": "实体1的类别"}, ...]。</div>
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Check our [paper](https://arxiv.org/abs/2406.17305) for more information. Check our [github repo](https://github.com/Emma1066/Retrieval-Augmented-IT-OpenNER) about how to use the model.
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## Inference
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The template for inference instances is as follows:
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<div style="background-color: #f6f8fa; padding: 20px; border-radius: 10px; border: 1px solid #e1e4e8; box-shadow: 0 2px 5px rgba(0,0,0,0.1);">
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<strong>Prompting template:</strong><br/>
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USER: 以下是一些命名实体识别的例子：<span style="color: #d73a49;">{Fill the NER examples here}</span><br/>
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ASSISTANT: 我已读完这些例子。<br/>
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USER: 文本：<span style="color: #d73a49;">{Fill the input text here}</span><br/>
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ASSISTANT: 我已读完这段文本。<br/>
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USER: 文本中属于"<span style="color: #d73a49;">{Fill the entity type here}</span> "的实体有哪些？<br/>
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ASSISTANT: <span style="color: #0366d6;">(model's predictions in JSON format)</span><br/>
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</div>
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Note:
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* The model can conduct inference **with and without** NER examples. If you want to conduct inference without examples, just start from the third line in the above template by directly inputting "文本：{input text}" in the "USER" role.
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* Inferences are based on one entity type at a time. For multiple entity types, create separate instances for each type.
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## License
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This model and its associated data are released under the [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) license. They are primarily used for research purposes.
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added_tokens.json
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config.json
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{
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"_name_or_path": "models/Qwen/Qwen1.5-7B-Chat",
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"Qwen2ForCausalLM"
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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||||
"model.layers.6.input_layernorm.weight": "model-00003-of-00008.safetensors",
|
||||
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|
||||
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||||
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||||
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|
||||
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||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
"model.norm.weight": "model-00008-of-00008.safetensors"
|
||||
}
|
||||
}
|
||||
20
special_tokens_map.json
Normal file
20
special_tokens_map.json
Normal file
@@ -0,0 +1,20 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>"
|
||||
],
|
||||
"eos_token": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
303112
tokenizer.json
Normal file
303112
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
44
tokenizer_config.json
Normal file
44
tokenizer_config.json
Normal file
@@ -0,0 +1,44 @@
|
||||
{
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151644": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151645": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"chat_template": "{% set system_message = 'You are a helpful assistant.' %}{% if messages[0]['role'] == 'system' %}{% set system_message = messages[0]['content'] %}{% endif %}{% if system_message is defined %}{{ '<|im_start|>system\n' + system_message + '<|im_end|>\n' }}{% endif %}{% for message in messages %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '<|im_start|>user\n' + content + '<|im_end|>\n<|im_start|>assistant\n' }}{% elif message['role'] == 'assistant' %}{{ content + '<|im_end|>' + '\n' }}{% endif %}{% endfor %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"model_max_length": 32768,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"padding_side": "left",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user