wqh
commited on
Commit
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Parent(s):
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add model file
Browse files- README.md +29 -0
- config.json +34 -0
- model.safetensors +3 -0
- sentencepiece.bpe.model +3 -0
- special_tokens_map.json +51 -0
- tokenizer_config.json +55 -0
- training_args.bin +3 -0
README.md
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# Model Card for GeoReranker
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The reranker is a critical component in Retrieval-Augmented Generation (RAG) systems, designed to refine the initial retrieval results by reordering candidate documents based on their semantic relevance to the query. Different from embedding model, reranker uses question and document as input and directly output similarity instead of embedding. You can get a relevance score by inputting query and passage to the reranker. And the score can be mapped to a float value in [0,1] by sigmoid function.
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## Quick Start
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To load the GeoReranker model with HuggingFace, use the following snippet:
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```python
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from FlagEmbedding import FlagReranker
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model_name_or_path = 'GeoGPT/GeoReranker'
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reranker = FlagReranker(model_name_or_path, use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
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score = reranker.compute_score(['query', 'passage'])
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# You can map the scores into 0-1 by set "normalize=True", which will apply sigmoid function to the score
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score = reranker.compute_score(['query', 'passage'], normalize=True)
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scores = reranker.compute_score([['what is panda?', 'hi'], ['what is panda?', 'The giant panda (Ailuropoda melanoleuca), sometimes called a panda bear or simply panda, is a bear species endemic to China.']])
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# You can map the scores into 0-1 by set "normalize=True", which will apply sigmoid function to the score
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scores = reranker.compute_score([['what is panda?', 'hi'], ['what is panda?', 'The giant panda (Ailuropoda melanoleuca), sometimes called a panda bear or simply panda, is a bear species endemic to China.']], normalize=True)
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```
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## License and Uses
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GeoReranker is licensed under the MIT License Agreement. The primary use of GeoGPT models is to support geoscience research, providing geoscientists with innovative tools and capabilities enhanced by large language models. It is specifically designed for non-commercial research and educational purposes.
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The model is not intended for use in any manner that violates applicable laws or regulations, nor for any activities prohibited by the license agreement. Additionally, it should not be used in languages other than those explicitly supported, as outlined in this model card.
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## Limitations
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GeoReranker is trained on English datasets, and performance may be suboptimal for other languages.
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config.json
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{
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"_name_or_path": "./bge-reranker-v2-m3",
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"architectures": [
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"XLMRobertaForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"eos_token_id": 2,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"id2label": {
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"0": "LABEL_0"
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},
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"label2id": {
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"LABEL_0": 0
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 8194,
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"model_type": "xlm-roberta",
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"output_past": true,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.41.2",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 250002
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:c561baf7c199acb0e311097a05c8b06bafdeb14e57a604a222a072a69d5b6b23
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size 2271071852
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sentencepiece.bpe.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865
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size 5069051
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"cls_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"mask_token": {
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"content": "<mask>",
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"lstrip": true,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": {
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"content": "<pad>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"sep_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer_config.json
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{
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"added_tokens_decoder": {
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"0": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"1": {
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"content": "<pad>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"2": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"3": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"250001": {
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"content": "<mask>",
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"lstrip": true,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"bos_token": "<s>",
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"clean_up_tokenization_spaces": true,
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"cls_token": "<s>",
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"eos_token": "</s>",
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"mask_token": "<mask>",
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"model_max_length": 8192,
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"pad_token": "<pad>",
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"sep_token": "</s>",
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"sp_model_kwargs": {},
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"tokenizer_class": "XLMRobertaTokenizer",
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"unk_token": "<unk>"
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}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:524dcf95d1bce82fe85d424e8f6612675954f9bd8800064479e0172351676ab7
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size 5176
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