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Model: zyznull/RankingGPT-llama2-7b Source: Original Platform
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README.md
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---
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license: mit
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---
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# RankingGPT-llama2-7b
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RankingGPT is a text ranker based on large language models with significant in-domain and out-domain effectiveness.
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We provide RankingGPT in different sizes and types, including bloom-560m, bloom-1b1, bloom-3b, bloom-7b, llama2-7b, baichuan2-7b and qwen-7b.
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More details please refer to our [paper](https://arxiv.org/abs/2311.16720) and [github](https://github.com/Alibaba-NLP/RankingGPT).
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## Usage
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Code example
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```python
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import torch
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from transformers import AutoModelForCausalLM, LlamaTokenizer
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tokenizer = LlamaTokenizer.from_pretrained('zyznull/RankingGPT-llama2-7b',trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained('zyznull/RankingGPT-llama2-7b',trust_remote_code=True).eval()
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query='when should a baby walk'
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document='Most babies start to walk around 13 months, but your baby may start walking as early as 9 or 10 months or as late as 15 or 16 months.'
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context=f'Document: {document} Query:'
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example=context+query
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context_enc = tokenizer.encode(context, add_special_tokens=False)
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continuation_enc = tokenizer.encode(query, add_special_tokens=False)
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model_input = torch.tensor(context_enc+continuation_enc[:-1])
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continuation_len = len(continuation_enc)
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input_len, = model_input.shape
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with torch.no_grad():
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logprobs = torch.nn.functional.log_softmax(model(model_input.unsqueeze(dim=0))[0], dim=-1)[0]
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logprobs = logprobs[input_len-continuation_len:]
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logprobs = torch.gather(logprobs, 1, torch.tensor(continuation_enc).unsqueeze(-1)).squeeze(-1)
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score = torch.sum(logprobs)/logprobs.shape[0]
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print(f"Document: {document[:20] + '...'} Score: {score}")
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```
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### Result
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| | DL19 | DL20 | BEIR | url |
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|---------|------|------|------|-----------------|
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| MonoBERT-340M | 72.3 | 70.3 | 50.5 | [huggingface](https://huggingface.co/veneres/monobert-msmarco) |
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| MonoT5-220M | 71.5 | 69.7 | 49.3 | [huggingface](https://huggingface.co/castorini/monot5-base-msmarco) |
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| MonoT5-770M | 73.2 | 71.2 | 53.1 | [huggingface](https://huggingface.co/castorini/monot5-large-msmarco) |
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| MonoT5-3B | 72.8 | 74.5 | 54.6 | [huggingface](https://huggingface.co/castorini/monot5-3b-msmarco) |
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| RankT5-770M | - | - | 53.7 | [huggingface](https://huggingface.co/bergum/rank-T5-flan) |
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| RankLLaMA| 74.6 | 76.6 | 52.5 | [huggingface](https://huggingface.co/castorini/rankllama-v1-7b-lora-passage) |
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| RankingGPT-bloom-560m| 75.3 | 73.2 | 53.7 | [huggingface](https://huggingface.co/zyznull/RankingGPT-bloom-560m) [modelscope](https://modelscope.cn/models/damo/RankingGPT-bloom-560m) |
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| RankingGPT-bloom-1b1| 75.6 | 73.2 | 54.5 | [huggingface](https://huggingface.co/zyznull/RankingGPT-bloom-1b1) [modelscope](https://modelscope.cn/models/damo/RankingGPT-bloom-1b1) |
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| RankingGPT-bloom-3b| 76.8 | 73.6 | 56.2 | [huggingface](https://huggingface.co/zyznull/RankingGPT-bloom-3b) [modelscope](https://modelscope.cn/models/damo/RankingGPT-bloom-3b) |
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| RankingGPT-bloom-7b| 77.3 | 74.6 | 56.6 | [huggingface](https://huggingface.co/zyznull/RankingGPT-bloom-7b) [modelscope](https://modelscope.cn/models/damo/RankingGPT-bloom-7b) |
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| RankingGPT-llama2-7b| 76.2 | 76.3 | 57.8 | [huggingface](https://huggingface.co/zyznull/RankingGPT-llama2-7b) [modelscope](https://modelscope.cn/models/damo/RankingGPT-llama2-7b) |
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| RankingGPT-baichuan2-7b| 75.9 | 74.3 | 57.5 | [huggingface](https://huggingface.co/zyznull/RankingGPT-baichuan2-7b) [modelscope](https://modelscope.cn/models/damo/RankingGPT-baichuan2-7b) |
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| RankingGPT-qwen-7b| 75.8 | 74.3 | 58.3 | [huggingface](https://huggingface.co/zyznull/RankingGPT-qwen-7b) [modelscope](https://modelscope.cn/models/damo/RankingGPT-qwen-7b) |
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### Citation
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If you find our paper or models helpful, please consider citing them as follows:
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```
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@misc{zhang2023rankinggpt,
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title={RankingGPT: Empowering Large Language Models in Text Ranking with Progressive Enhancement},
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author={Longhui Zhang and Yanzhao Zhang and Dingkun Long and Pengjun Xie and Meishan Zhang and Min Zhang},
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year={2023},
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eprint={2311.16720},
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archivePrefix={arXiv},
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primaryClass={cs.IR}
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}
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```
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config.json
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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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||||
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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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|
||||
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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": "pytorch_model-00002-of-00002.bin"
|
||||
}
|
||||
}
|
||||
24
special_tokens_map.json
Normal file
24
special_tokens_map.json
Normal file
@@ -0,0 +1,24 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": "<unk>",
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
Binary file not shown.
35
tokenizer_config.json
Normal file
35
tokenizer_config.json
Normal file
@@ -0,0 +1,35 @@
|
||||
{
|
||||
"add_bos_token": true,
|
||||
"add_eos_token": false,
|
||||
"bos_token": {
|
||||
"__type": "AddedToken",
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": {
|
||||
"__type": "AddedToken",
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"legacy": false,
|
||||
"model_max_length": 512,
|
||||
"pad_token": null,
|
||||
"padding_side": "right",
|
||||
"sp_model_kwargs": {},
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": {
|
||||
"__type": "AddedToken",
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user