fabiannagel
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Browse filesConfigured German model added
- .gitattributes +1 -0
- 1_Dense/config.json +1 -0
- 1_Dense/model.safetensors +3 -0
- config.json +116 -0
- config_sentence_transformers.json +49 -0
- convert_model.py +25 -0
- model.md +144 -0
- model.safetensors +3 -0
- modules.json +14 -0
- sentence_bert_config.json +4 -0
- special_tokens_map.json +45 -0
- tokenizer.json +3 -0
- tokenizer_config.json +70 -0
.gitattributes
CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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1_Dense/config.json
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{"in_features": 768, "out_features": 128, "bias": false, "activation_function": "torch.nn.modules.linear.Identity"}
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1_Dense/model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:082cc1e4b9bf47d7eb8979a9e2cc643f3c3ea07dc68a706c58823316235025e1
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size 393304
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config.json
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@@ -0,0 +1,116 @@
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{
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"_name_or_path": "antoinelouis/colbert-xm",
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"adapter_layer_norm": false,
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"adapter_reduction_factor": 2,
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"adapter_reuse_layer_norm": true,
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"architectures": [
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"XmodModel"
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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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"default_language": "de_DE",
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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": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"languages": [
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"en_XX",
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"id_ID",
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"vi_VN",
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"ru_RU",
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"fa_IR",
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"sv_SE",
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"ja_XX",
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"fr_XX",
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"de_DE",
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"ro_RO",
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"ko_KR",
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"hu_HU",
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"es_XX",
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"fi_FI",
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"uk_UA",
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"da_DK",
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"pt_XX",
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"no_XX",
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"th_TH",
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"pl_PL",
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"bg_BG",
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"nl_XX",
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"zh_CN",
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"he_IL",
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"el_GR",
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"it_IT",
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"sk_SK",
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"hr_HR",
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"tr_TR",
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"ar_AR",
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"cs_CZ",
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"lt_LT",
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"hi_IN",
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"zh_TW",
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"ca_ES",
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"ms_MY",
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"sl_SI",
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"lv_LV",
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"ta_IN",
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"bn_IN",
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"et_EE",
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"az_AZ",
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"sq_AL",
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"sr_RS",
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"kk_KZ",
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"ka_GE",
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"tl_XX",
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"ur_PK",
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"is_IS",
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"hy_AM",
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"ml_IN",
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"mk_MK",
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"be_BY",
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"la_VA",
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"te_IN",
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"eu_ES",
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"gl_ES",
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"mn_MN",
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"kn_IN",
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"ne_NP",
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"sw_KE",
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"si_LK",
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"mr_IN",
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"af_ZA",
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"gu_IN",
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"cy_GB",
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"eo_EO",
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"km_KH",
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"ky_KG",
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"uz_UZ",
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"ps_AF",
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"pa_IN",
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"ga_IE",
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"ha_NG",
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"am_ET",
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"lo_LA",
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"ku_TR",
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"so_SO",
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"my_MM",
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"or_IN",
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"sa_IN"
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],
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"layer_norm_eps": 1e-05,
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"ln_before_adapter": true,
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"max_position_embeddings": 514,
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"model_type": "xmod",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"pre_norm": false,
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"torch_dtype": "float32",
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"transformers_version": "4.45.1",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 250004
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}
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config_sentence_transformers.json
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{
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"__version__": {
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"sentence_transformers": "3.0.1",
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"transformers": "4.45.1",
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"pytorch": "2.4.1"
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},
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"prompts": {},
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"default_prompt_name": null,
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"similarity_fn_name": null,
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"query_prefix": "[unused0]",
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"document_prefix": "[unused1]",
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"query_length": 32,
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"document_length": 180,
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"attend_to_expansion_tokens": false,
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"skiplist_words": [
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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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"}",
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"~"
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]
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}
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convert_model.py
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from pylate import models
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# pip install pylate==1.1.2
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def get_pylate_model(language: str, train: bool) -> 'pylate.models.ColBERT':
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"""
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Configures the antoinelouis/colbert-xm model for usage with PyLate
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See discussion here: https://github.com/lightonai/pylate/discussions/50#discussioncomment-10691630
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For language, use a code from https://huggingface.co/facebook/xmod-base#languages
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"""
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colbert_model = models.ColBERT(model_name_or_path='antoinelouis/colbert-xm')
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backbone = colbert_model[0].auto_model
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if backbone.__class__.__name__.lower().startswith("xmod"):
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backbone.set_default_language(language)
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if train:
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backbone.freeze_embeddings_and_language_adapters()
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training = '' if not train else '_train'
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colbert_model.save_pretrained(f'pylate-colbert-xm-{language}{training}/')
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if __name__ == '__main__':
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get_pylate_model(language='de_DE', train=False)
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model.md
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---
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base_model: antoinelouis/colbert-xm
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datasets: []
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language: []
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library_name: sentence-transformers
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pipeline_tag: sentence-similarity
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tags:
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- sentence-transformers
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- sentence-similarity
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- feature-extraction
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widget: []
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---
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# SentenceTransformer based on antoinelouis/colbert-xm
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This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [antoinelouis/colbert-xm](https://huggingface.co/antoinelouis/colbert-xm). It maps sentences & paragraphs to a 128-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
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## Model Details
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### Model Description
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- **Model Type:** Sentence Transformer
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- **Base model:** [antoinelouis/colbert-xm](https://huggingface.co/antoinelouis/colbert-xm) <!-- at revision f406563b621f86d96899d4652dfbc562692bb526 -->
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- **Maximum Sequence Length:** 514 tokens
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- **Output Dimensionality:** 128 tokens
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- **Similarity Function:** Cosine Similarity
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<!-- - **Training Dataset:** Unknown -->
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<!-- - **Language:** Unknown -->
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<!-- - **License:** Unknown -->
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### Model Sources
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- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
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- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
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- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
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### Full Model Architecture
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```
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ColBERT(
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(0): Transformer({'max_seq_length': 514, 'do_lower_case': False}) with Transformer model: XmodModel
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(1): Dense({'in_features': 768, 'out_features': 128, 'bias': False, 'activation_function': 'torch.nn.modules.linear.Identity'})
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)
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```
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## Usage
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46 |
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### Direct Usage (Sentence Transformers)
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First install the Sentence Transformers library:
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|
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```bash
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pip install -U sentence-transformers
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```
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Then you can load this model and run inference.
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```python
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from sentence_transformers import SentenceTransformer
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# Download from the 🤗 Hub
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model = SentenceTransformer("sentence_transformers_model_id")
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# Run inference
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sentences = [
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'The weather is lovely today.',
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"It's so sunny outside!",
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'He drove to the stadium.',
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]
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embeddings = model.encode(sentences)
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print(embeddings.shape)
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# [3, 128]
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# Get the similarity scores for the embeddings
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similarities = model.similarity(embeddings, embeddings)
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print(similarities.shape)
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# [3, 3]
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```
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|
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<!--
|
78 |
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### Direct Usage (Transformers)
|
79 |
+
|
80 |
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<details><summary>Click to see the direct usage in Transformers</summary>
|
81 |
+
|
82 |
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</details>
|
83 |
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-->
|
84 |
+
|
85 |
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<!--
|
86 |
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### Downstream Usage (Sentence Transformers)
|
87 |
+
|
88 |
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You can finetune this model on your own dataset.
|
89 |
+
|
90 |
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<details><summary>Click to expand</summary>
|
91 |
+
|
92 |
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</details>
|
93 |
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-->
|
94 |
+
|
95 |
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<!--
|
96 |
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### Out-of-Scope Use
|
97 |
+
|
98 |
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*List how the model may foreseeably be misused and address what users ought not to do with the model.*
|
99 |
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-->
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+
<!--
|
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+
## Bias, Risks and Limitations
|
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+
|
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+
*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
|
105 |
+
-->
|
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+
|
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+
<!--
|
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### Recommendations
|
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+
|
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+
*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
|
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+
-->
|
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+
|
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+
## Training Details
|
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+
|
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+
### Framework Versions
|
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+
- Python: 3.12.5
|
117 |
+
- Sentence Transformers: 3.0.1
|
118 |
+
- Transformers: 4.45.1
|
119 |
+
- PyTorch: 2.4.1
|
120 |
+
- Accelerate: 0.34.2
|
121 |
+
- Datasets: 3.0.1
|
122 |
+
- Tokenizers: 0.20.0
|
123 |
+
|
124 |
+
## Citation
|
125 |
+
|
126 |
+
### BibTeX
|
127 |
+
|
128 |
+
<!--
|
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+
## Glossary
|
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+
|
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+
*Clearly define terms in order to be accessible across audiences.*
|
132 |
+
-->
|
133 |
+
|
134 |
+
<!--
|
135 |
+
## Model Card Authors
|
136 |
+
|
137 |
+
*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
|
138 |
+
-->
|
139 |
+
|
140 |
+
<!--
|
141 |
+
## Model Card Contact
|
142 |
+
|
143 |
+
*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
|
144 |
+
-->
|
model.safetensors
ADDED
@@ -0,0 +1,3 @@
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|
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version https://git-lfs.github.com/spec/v1
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size 3410427464
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modules.json
ADDED
@@ -0,0 +1,14 @@
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|
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[
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{
|
3 |
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"idx": 0,
|
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"name": "0",
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|
6 |
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"type": "sentence_transformers.models.Transformer"
|
7 |
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},
|
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{
|
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|
10 |
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"name": "1",
|
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"path": "1_Dense",
|
12 |
+
"type": "pylate.models.Dense"
|
13 |
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}
|
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+
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|
sentence_bert_config.json
ADDED
@@ -0,0 +1,4 @@
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|
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|
|
1 |
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{
|
2 |
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"max_seq_length": 514,
|
3 |
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"do_lower_case": false
|
4 |
+
}
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special_tokens_map.json
ADDED
@@ -0,0 +1,45 @@
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|
1 |
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{
|
2 |
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"bos_token": {
|
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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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|
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|
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|
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|
44 |
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|
45 |
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}
|
tokenizer.json
ADDED
@@ -0,0 +1,3 @@
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|
|
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|
|
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|
1 |
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version https://git-lfs.github.com/spec/v1
|
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oid sha256:410ff101f2c7d6eb4f670a9410e9e27063dc10cd0c82fb1925ee779788d3036d
|
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size 17083106
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tokenizer_config.json
ADDED
@@ -0,0 +1,70 @@
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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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|
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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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