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* Add model 2023-04-13-CyberbullyingDetection_ClassifierDL_tfhub_en (#13757)

Co-authored-by: Naveen-004 <chinna.nk4@gmail.com>

* 2023-04-20-distilbert_base_uncased_mnli_en (#13761)

* Add model 2023-04-20-distilbert_base_uncased_mnli_en

* Add model 2023-04-20-distilbert_base_turkish_cased_allnli_tr

* Add model 2023-04-20-distilbert_base_turkish_cased_snli_tr

* Add model 2023-04-20-distilbert_base_turkish_cased_multinli_tr

* Update and rename 2023-04-20-distilbert_base_turkish_cased_allnli_tr.md to 2023-04-20-distilbert_base_zero_shot_classifier_turkish_cased_allnli_tr.md

* Update and rename 2023-04-20-distilbert_base_turkish_cased_multinli_tr.md to 2023-04-20-distilbert_base_zero_shot_classifier_turkish_cased_multinli_tr.md

* Update and rename 2023-04-20-distilbert_base_turkish_cased_snli_tr.md to 2023-04-20-distilbert_base_zero_shot_classifier_turkish_cased_snli_tr.md

* Update and rename 2023-04-20-distilbert_base_uncased_mnli_en.md to distilbert_base_zero_shot_classifier_turkish_cased_snli

* Rename distilbert_base_zero_shot_classifier_turkish_cased_snli to distilbert_base_zero_shot_classifier_turkish_cased_snli_en.md

* Update 2023-04-20-distilbert_base_zero_shot_classifier_turkish_cased_snli_tr.md

* Update 2023-04-20-distilbert_base_zero_shot_classifier_turkish_cased_multinli_tr.md

* Update 2023-04-20-distilbert_base_zero_shot_classifier_turkish_cased_allnli_tr.md

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Co-authored-by: ahmedlone127 <ahmedlone127@gmail.com>

* 2023-04-20-distilbert_base_zero_shot_classifier_turkish_cased_multinli_tr (#13763)

* Add model 2023-04-20-distilbert_base_zero_shot_classifier_turkish_cased_multinli_tr

* Add model 2023-04-20-distilbert_base_zero_shot_classifier_uncased_mnli_en

* Add model 2023-04-20-distilbert_base_zero_shot_classifier_turkish_cased_snli_tr

* Add model 2023-04-20-distilbert_base_zero_shot_classifier_turkish_cased_allnli_tr

* Update 2023-04-20-distilbert_base_zero_shot_classifier_turkish_cased_multinli_tr.md

* Update 2023-04-20-distilbert_base_zero_shot_classifier_turkish_cased_snli_tr.md

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Co-authored-by: ahmedlone127 <ahmedlone127@gmail.com>

* 2023-05-04-roberta_base_zero_shot_classifier_nli_en (#13781)

* Add model 2023-05-04-roberta_base_zero_shot_classifier_nli_en

* Fix Spark version to 3.0

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Co-authored-by: ahmedlone127 <ahmedlone127@gmail.com>
Co-authored-by: Maziyar Panahi <maziyar.panahi@iscpif.fr>

* 2023-05-09-distilbart_xsum_6_6_en (#13788)

* Add model 2023-05-09-distilbart_xsum_6_6_en

* Add model 2023-05-09-distilbart_xsum_12_6_en

* Add model 2023-05-09-distilbart_cnn_12_6_en

* Add model 2023-05-09-distilbart_cnn_6_6_en

* Add model 2023-05-09-bart_large_cnn_en

* Update 2023-05-09-bart_large_cnn_en.md

* Update 2023-05-09-distilbart_cnn_12_6_en.md

* Update 2023-05-09-distilbart_cnn_6_6_en.md

* Update 2023-05-09-distilbart_xsum_12_6_en.md

* Update 2023-05-09-distilbart_xsum_6_6_en.md

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Co-authored-by: prabod <prabod@rathnayaka.me>
Co-authored-by: Maziyar Panahi <maziyar.panahi@iscpif.fr>

* 2023-05-11-distilbart_cnn_12_6_en (#13795)

* Add model 2023-05-11-distilbart_cnn_12_6_en

* Add model 2023-05-11-distilbart_cnn_6_6_en

* Add model 2023-05-11-distilbart_xsum_12_6_en

* Add model 2023-05-11-distilbart_xsum_6_6_en

* Add model 2023-05-11-bart_large_cnn_en

* Update 2023-05-11-bart_large_cnn_en.md

* Update 2023-05-11-distilbart_cnn_12_6_en.md

* Update 2023-05-11-distilbart_cnn_6_6_en.md

* Update 2023-05-11-distilbart_xsum_12_6_en.md

* Update 2023-05-11-distilbart_xsum_6_6_en.md

---------

Co-authored-by: prabod <prabod@rathnayaka.me>
Co-authored-by: Maziyar Panahi <maziyar.panahi@iscpif.fr>

* 2023-05-19-match_pattern_en (#13805)

* Add model 2023-05-19-match_pattern_en

* Add model 2023-05-19-dependency_parse_en

* Add model 2023-05-20-explain_document_md_fr

* Add model 2023-05-20-dependency_parse_en

* Add model 2023-05-20-explain_document_md_it

* Add model 2023-05-20-entity_recognizer_lg_fr

* Add model 2023-05-20-entity_recognizer_md_fr

* Add model 2023-05-20-entity_recognizer_lg_it

* Add model 2023-05-20-entity_recognizer_md_it

* Add model 2023-05-20-check_spelling_en

* Add model 2023-05-20-match_datetime_en

* Add model 2023-05-20-match_pattern_en

* Add model 2023-05-20-clean_pattern_en

* Add model 2023-05-20-clean_stop_en

* Add model 2023-05-20-movies_sentiment_analysis_en

* Add model 2023-05-20-explain_document_ml_en

* Add model 2023-05-20-analyze_sentiment_en

* Add model 2023-05-20-explain_document_dl_en

* Add model 2023-05-20-recognize_entities_dl_en

* Add model 2023-05-20-recognize_entities_bert_en

* Add model 2023-05-20-explain_document_md_de

* Add model 2023-05-21-entity_recognizer_lg_de

* Add model 2023-05-21-entity_recognizer_md_de

* Add model 2023-05-21-onto_recognize_entities_sm_en

* Add model 2023-05-21-onto_recognize_entities_lg_en

* Add model 2023-05-21-match_chunks_en

* Add model 2023-05-21-explain_document_lg_es

* Add model 2023-05-21-explain_document_md_es

* Add model 2023-05-21-explain_document_sm_es

* Add model 2023-05-21-entity_recognizer_lg_es

* Add model 2023-05-21-entity_recognizer_md_es

* Add model 2023-05-21-entity_recognizer_sm_es

* Add model 2023-05-21-explain_document_lg_ru

* Add model 2023-05-21-explain_document_md_ru

* Add model 2023-05-21-explain_document_sm_ru

* Add model 2023-05-21-entity_recognizer_lg_ru

* Add model 2023-05-21-entity_recognizer_md_ru

* Add model 2023-05-21-entity_recognizer_sm_ru

* Add model 2023-05-21-text_cleaning_en

* Add model 2023-05-21-explain_document_lg_pt

* Add model 2023-05-21-explain_document_md_pt

* Add model 2023-05-21-explain_document_sm_pt

* Add model 2023-05-21-entity_recognizer_lg_pt

* Add model 2023-05-21-entity_recognizer_md_pt

* Add model 2023-05-21-entity_recognizer_sm_pt

* Add model 2023-05-21-explain_document_lg_pl

* Add model 2023-05-21-explain_document_md_pl

* Add model 2023-05-21-explain_document_sm_pl

* Add model 2023-05-21-entity_recognizer_lg_pl

* Add model 2023-05-21-entity_recognizer_md_pl

* Add model 2023-05-21-entity_recognizer_sm_pl

* Add model 2023-05-21-explain_document_lg_nl

* Add model 2023-05-21-explain_document_md_nl

* Add model 2023-05-21-explain_document_sm_nl

* Add model 2023-05-21-entity_recognizer_lg_nl

* Add model 2023-05-21-entity_recognizer_md_nl

* Add model 2023-05-21-entity_recognizer_sm_nl

* Add model 2023-05-21-analyze_sentimentdl_glove_imdb_en

* Add model 2023-05-21-explain_document_lg_no

* Add model 2023-05-21-explain_document_md_no

* Add model 2023-05-21-explain_document_sm_no

* Add model 2023-05-21-entity_recognizer_lg_no

* Add model 2023-05-21-entity_recognizer_md_no

* Add model 2023-05-21-entity_recognizer_sm_no

* Add model 2023-05-21-explain_document_lg_sv

* Add model 2023-05-21-explain_document_md_sv

* Add model 2023-05-21-explain_document_sm_sv

* Add model 2023-05-21-entity_recognizer_lg_sv

* Add model 2023-05-21-entity_recognizer_md_sv

* Add model 2023-05-21-entity_recognizer_sm_sv

* Add model 2023-05-21-explain_document_lg_da

* Add model 2023-05-21-explain_document_md_da

* Add model 2023-05-21-explain_document_sm_da

* Add model 2023-05-21-entity_recognizer_lg_da

* Add model 2023-05-21-entity_recognizer_md_da

* Add model 2023-05-21-entity_recognizer_sm_da

* Add model 2023-05-21-explain_document_lg_fi

* Add model 2023-05-21-explain_document_md_fi

* Add model 2023-05-21-explain_document_sm_fi

* Add model 2023-05-21-entity_recognizer_lg_fi

* Add model 2023-05-21-entity_recognizer_md_fi

* Add model 2023-05-21-entity_recognizer_sm_fi

* Add model 2023-05-21-onto_recognize_entities_bert_base_en

* Add model 2023-05-21-onto_recognize_entities_bert_large_en

* Add model 2023-05-21-onto_recognize_entities_bert_medium_en

* Add model 2023-05-21-onto_recognize_entities_bert_mini_en

* Add model 2023-05-21-onto_recognize_entities_bert_small_en

* Add model 2023-05-21-onto_recognize_entities_bert_tiny_en

* Add model 2023-05-21-onto_recognize_entities_electra_base_en

* Add model 2023-05-21-onto_recognize_entities_electra_small_en

* Add model 2023-05-21-onto_recognize_entities_electra_large_en

* Add model 2023-05-21-recognize_entities_dl_fa

* Add model 2023-05-21-nerdl_fewnerd_subentity_100d_pipeline_en

* Add model 2023-05-21-nerdl_fewnerd_100d_pipeline_en

* Add model 2023-05-21-pos_ud_bokmaal_nb

* Add model 2023-05-21-xlm_roberta_large_token_classifier_masakhaner_pipeline_xx

* Add model 2023-05-21-bert_token_classifier_scandi_ner_pipeline_xx

* Add model 2023-05-21-bert_sequence_classifier_trec_coarse_pipeline_en

* Add model 2023-05-21-bert_sequence_classifier_age_news_pipeline_en

* Add model 2023-05-21-distilbert_token_classifier_typo_detector_pipeline_is

* Add model 2023-05-21-distilbert_base_token_classifier_masakhaner_pipeline_xx

* Add model 2023-05-21-nerdl_restaurant_100d_pipeline_en

* Add model 2023-05-21-roberta_token_classifier_timex_semeval_pipeline_en

* Add model 2023-05-21-bert_token_classifier_hi_en_ner_pipeline_hi

* Add model 2023-05-21-xlm_roberta_large_token_classifier_hrl_pipeline_xx

* Add model 2023-05-21-spellcheck_dl_pipeline_en

* Add model 2023-05-21-bert_token_classifier_dutch_udlassy_ner_pipeline_nl

* Add model 2023-05-21-xlm_roberta_large_token_classifier_conll03_pipeline_de

* Add model 2023-05-21-roberta_token_classifier_bne_capitel_ner_pipeline_es

* Add model 2023-05-21-roberta_token_classifier_icelandic_ner_pipeline_is

* Add model 2023-05-21-longformer_base_token_classifier_conll03_pipeline_en

* Add model 2023-05-21-longformer_large_token_classifier_conll03_pipeline_en

* Add model 2023-05-21-xlnet_base_token_classifier_conll03_pipeline_en

* Add model 2023-05-21-xlm_roberta_base_token_classifier_ontonotes_pipeline_en

* Add model 2023-05-21-xlm_roberta_base_token_classifier_conll03_pipeline_en

* Add model 2023-05-21-xlnet_large_token_classifier_conll03_pipeline_en

* Add model 2023-05-21-albert_base_token_classifier_conll03_pipeline_en

* Add model 2023-05-21-albert_large_token_classifier_conll03_pipeline_en

* Add model 2023-05-21-albert_xlarge_token_classifier_conll03_pipeline_en

* Add model 2023-05-21-distilroberta_base_token_classifier_ontonotes_pipeline_en

* Add model 2023-05-21-roberta_base_token_classifier_ontonotes_pipeline_en

* Add model 2023-05-21-roberta_large_token_classifier_conll03_pipeline_en

* Add model 2023-05-21-distilbert_token_classifier_typo_detector_pipeline_en

---------

Co-authored-by: ahmedlone127 <ahmedlone127@gmail.com>

* 2023-05-22-explain_document_md_fr (#13811)

* Add model 2023-05-22-explain_document_md_fr

* Add model 2023-05-22-dependency_parse_en

* Add model 2023-05-22-explain_document_md_it

* Add model 2023-05-22-entity_recognizer_lg_fr

* Add model 2023-05-22-entity_recognizer_md_fr

* Add model 2023-05-22-entity_recognizer_lg_it

* Add model 2023-05-22-entity_recognizer_md_it

* Add model 2023-05-22-check_spelling_en

* Add model 2023-05-22-match_datetime_en

* Add model 2023-05-22-match_pattern_en

* Add model 2023-05-22-clean_pattern_en

* Add model 2023-05-22-clean_stop_en

* Add model 2023-05-22-movies_sentiment_analysis_en

* Add model 2023-05-22-explain_document_ml_en

* Add model 2023-05-22-analyze_sentiment_en

* Add model 2023-05-22-explain_document_dl_en

* Add model 2023-05-22-recognize_entities_dl_en

* Add model 2023-05-22-recognize_entities_bert_en

* Add model 2023-05-22-explain_document_md_de

* Add model 2023-05-22-entity_recognizer_lg_de

* Add model 2023-05-22-entity_recognizer_md_de

* Add model 2023-05-22-onto_recognize_entities_sm_en

* Add model 2023-05-22-onto_recognize_entities_lg_en

* Add model 2023-05-22-match_chunks_en

* Add model 2023-05-22-explain_document_lg_es

* Add model 2023-05-22-explain_document_md_es

* Add model 2023-05-22-explain_document_sm_es

* Add model 2023-05-22-entity_recognizer_lg_es

* Add model 2023-05-22-entity_recognizer_md_es

* Add model 2023-05-22-entity_recognizer_sm_es

* Add model 2023-05-22-explain_document_lg_ru

* Add model 2023-05-22-explain_document_md_ru

* Add model 2023-05-22-explain_document_sm_ru

* Add model 2023-05-22-entity_recognizer_lg_ru

* Add model 2023-05-22-entity_recognizer_md_ru

* Add model 2023-05-22-entity_recognizer_sm_ru

* Add model 2023-05-22-text_cleaning_en

* Add model 2023-05-22-explain_document_lg_pt

* Add model 2023-05-22-explain_document_md_pt

* Add model 2023-05-22-explain_document_sm_pt

* Add model 2023-05-22-entity_recognizer_lg_pt

* Add model 2023-05-22-entity_recognizer_md_pt

* Add model 2023-05-22-entity_recognizer_sm_pt

* Add model 2023-05-22-explain_document_lg_pl

* Add model 2023-05-22-explain_document_md_pl

* Add model 2023-05-22-explain_document_sm_pl

* Add model 2023-05-22-entity_recognizer_lg_pl

* Add model 2023-05-22-entity_recognizer_md_pl

* Add model 2023-05-22-entity_recognizer_sm_pl

* Add model 2023-05-22-explain_document_lg_nl

* Add model 2023-05-22-explain_document_md_nl

* Add model 2023-05-22-explain_document_sm_nl

* Add model 2023-05-22-entity_recognizer_lg_nl

* Add model 2023-05-22-entity_recognizer_md_nl

* Add model 2023-05-22-entity_recognizer_sm_nl

* Add model 2023-05-22-analyze_sentimentdl_glove_imdb_en

* Add model 2023-05-22-explain_document_lg_no

* Add model 2023-05-22-explain_document_md_no

* Add model 2023-05-22-explain_document_sm_no

* Add model 2023-05-22-entity_recognizer_md_no

* Add model 2023-05-22-entity_recognizer_sm_no

* Add model 2023-05-22-explain_document_lg_sv

* Add model 2023-05-22-explain_document_md_sv

* Add model 2023-05-22-explain_document_sm_sv

* Add model 2023-05-22-entity_recognizer_lg_sv

* Add model 2023-05-22-entity_recognizer_md_sv

* Add model 2023-05-22-entity_recognizer_sm_sv

* Add model 2023-05-22-explain_document_lg_da

* Add model 2023-05-22-explain_document_md_da

* Add model 2023-05-22-explain_document_sm_da

* Add model 2023-05-22-entity_recognizer_lg_da

* Add model 2023-05-22-entity_recognizer_md_da

* Add model 2023-05-22-entity_recognizer_sm_da

* Add model 2023-05-22-explain_document_lg_fi

* Add model 2023-05-22-explain_document_md_fi

* Add model 2023-05-22-explain_document_sm_fi

* Add model 2023-05-22-entity_recognizer_lg_fi

* Add model 2023-05-22-entity_recognizer_md_fi

* Add model 2023-05-22-entity_recognizer_sm_fi

* Add model 2023-05-22-onto_recognize_entities_bert_base_en

* Add model 2023-05-22-onto_recognize_entities_bert_large_en

* Add model 2023-05-22-onto_recognize_entities_bert_medium_en

* Add model 2023-05-22-onto_recognize_entities_bert_mini_en

* Add model 2023-05-22-onto_recognize_entities_bert_small_en

* Add model 2023-05-22-onto_recognize_entities_bert_tiny_en

* Add model 2023-05-22-onto_recognize_entities_electra_base_en

* Add model 2023-05-22-onto_recognize_entities_electra_small_en

* Add model 2023-05-22-onto_recognize_entities_electra_large_en

* Add model 2023-05-22-recognize_entities_dl_fa

* Add model 2023-05-22-nerdl_fewnerd_subentity_100d_pipeline_en

* Add model 2023-05-22-nerdl_fewnerd_100d_pipeline_en

* Add model 2023-05-22-pos_ud_bokmaal_nb

* Add model 2023-05-22-xlm_roberta_large_token_classifier_masakhaner_pipeline_xx

* Add model 2023-05-22-bert_token_classifier_scandi_ner_pipeline_xx

* Add model 2023-05-22-bert_sequence_classifier_trec_coarse_pipeline_en

* Add model 2023-05-22-bert_sequence_classifier_age_news_pipeline_en

* Add model 2023-05-22-distilbert_token_classifier_typo_detector_pipeline_is

* Add model 2023-05-22-distilbert_base_token_classifier_masakhaner_pipeline_xx

* Add model 2023-05-22-nerdl_restaurant_100d_pipeline_en

* Add model 2023-05-22-roberta_token_classifier_timex_semeval_pipeline_en

* Add model 2023-05-22-bert_token_classifier_hi_en_ner_pipeline_hi

* Add model 2023-05-22-xlm_roberta_large_token_classifier_hrl_pipeline_xx

* Add model 2023-05-22-spellcheck_dl_pipeline_en

* Add model 2023-05-22-bert_token_classifier_dutch_udlassy_ner_pipeline_nl

* Add model 2023-05-22-xlm_roberta_large_token_classifier_conll03_pipeline_de

* Add model 2023-05-22-roberta_token_classifier_bne_capitel_ner_pipeline_es

* Add model 2023-05-22-roberta_token_classifier_icelandic_ner_pipeline_is

* Add model 2023-05-22-longformer_base_token_classifier_conll03_pipeline_en

* Add model 2023-05-22-longformer_large_token_classifier_conll03_pipeline_en

* Add model 2023-05-22-xlnet_base_token_classifier_conll03_pipeline_en

* Add model 2023-05-22-xlm_roberta_base_token_classifier_ontonotes_pipeline_en

* Add model 2023-05-22-xlm_roberta_base_token_classifier_conll03_pipeline_en

* Add model 2023-05-22-xlnet_large_token_classifier_conll03_pipeline_en

* Add model 2023-05-22-albert_base_token_classifier_conll03_pipeline_en

* Add model 2023-05-22-albert_large_token_classifier_conll03_pipeline_en

* Add model 2023-05-22-albert_xlarge_token_classifier_conll03_pipeline_en

* Add model 2023-05-22-distilroberta_base_token_classifier_ontonotes_pipeline_en

* Add model 2023-05-22-roberta_base_token_classifier_ontonotes_pipeline_en

* Add model 2023-05-22-roberta_large_token_classifier_conll03_pipeline_en

* Add model 2023-05-22-distilbert_token_classifier_typo_detector_pipeline_en

---------

Co-authored-by: ahmedlone127 <ahmedlone127@gmail.com>

* 2023-05-24-explain_document_md_fr (#13821)

* Add model 2023-05-24-explain_document_md_fr

* Add model 2023-05-24-dependency_parse_en

* Add model 2023-05-24-explain_document_md_it

* Add model 2023-05-24-entity_recognizer_lg_fr

* Add model 2023-05-24-entity_recognizer_md_fr

* Add model 2023-05-24-entity_recognizer_lg_it

* Add model 2023-05-24-entity_recognizer_md_it

* Add model 2023-05-24-check_spelling_en

* Add model 2023-05-24-match_datetime_en

* Add model 2023-05-24-match_pattern_en

* Add model 2023-05-24-clean_pattern_en

* Add model 2023-05-24-clean_stop_en

* Add model 2023-05-24-movies_sentiment_analysis_en

* Add model 2023-05-24-explain_document_ml_en

* Add model 2023-05-24-analyze_sentiment_en

* Add model 2023-05-24-explain_document_dl_en

* Add model 2023-05-24-recognize_entities_dl_en

* Add model 2023-05-24-recognize_entities_bert_en

* Add model 2023-05-24-explain_document_md_de

* Add model 2023-05-24-entity_recognizer_lg_de

* Add model 2023-05-24-entity_recognizer_md_de

* Add model 2023-05-24-onto_recognize_entities_sm_en

* Add model 2023-05-24-onto_recognize_entities_lg_en

* Add model 2023-05-24-match_chunks_en

* Add model 2023-05-24-explain_document_lg_es

* Add model 2023-05-24-explain_document_md_es

* Add model 2023-05-24-explain_document_sm_es

* Add model 2023-05-24-entity_recognizer_lg_es

* Add model 2023-05-24-entity_recognizer_md_es

* Add model 2023-05-24-entity_recognizer_sm_es

* Add model 2023-05-24-explain_document_lg_ru

* Add model 2023-05-24-explain_document_md_ru

* Add model 2023-05-24-explain_document_sm_ru

* Add model 2023-05-24-entity_recognizer_lg_ru

* Add model 2023-05-24-entity_recognizer_md_ru

* Add model 2023-05-24-entity_recognizer_sm_ru

* Add model 2023-05-24-text_cleaning_en

* Add model 2023-05-24-explain_document_lg_pt

* Add model 2023-05-24-explain_document_md_pt

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---------

Co-authored-by: ahmedlone127 <ahmedlone127@gmail.com>

* Add model 2023-05-25-explain_document_md_fr (#13827)

Co-authored-by: ahmedlone127 <ahmedlone127@gmail.com>

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---------

Co-authored-by: ahmedlone127 <ahmedlone127@gmail.com>

---------

Co-authored-by: jsl-models <74001263+jsl-models@users.noreply.github.com>
Co-authored-by: Naveen-004 <chinna.nk4@gmail.com>
Co-authored-by: ahmedlone127 <ahmedlone127@gmail.com>
Co-authored-by: prabod <prabod@rathnayaka.me>
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130 changes: 130 additions & 0 deletions docs/_posts/ahmedlone127/2023-05-25-analyze_sentiment_en.md
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---
layout: model
title: Sentiment Analysis pipeline for English
author: John Snow Labs
name: analyze_sentiment
date: 2023-05-25
tags: [open_source, english, analyze_sentiment, pipeline, en]
task: Named Entity Recognition
language: en
edition: Spark NLP 4.4.2
spark_version: 3.4
supported: true
annotator: PipelineModel
article_header:
type: cover
use_language_switcher: "Python-Scala-Java"
---

## Description

The analyze_sentiment is a pretrained pipeline that we can use to process text with a simple pipeline that performs basic processing steps
and recognizes entities .
It performs most of the common text processing tasks on your dataframe

## Predicted Entities



{:.btn-box}
<button class="button button-orange" disabled>Live Demo</button>
<button class="button button-orange" disabled>Open in Colab</button>
[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/analyze_sentiment_en_4.4.2_3.4_1685040876208.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/analyze_sentiment_en_4.4.2_3.4_1685040876208.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

## How to use

<div class="tabs-box" markdown="1">
{% include programmingLanguageSelectScalaPythonNLU.html %}

```python

from sparknlp.pretrained import PretrainedPipeline

pipeline = PretrainedPipeline('analyze_sentiment', lang = 'en')

result = pipeline.fullAnnotate("""Demonicus is a movie turned into a video game! I just love the story and the things that goes on in the film.It is a B-film ofcourse but that doesn`t bother one bit because its made just right and the music was rad! Horror and sword fight freaks,buy this movie now!""")


```
```scala

import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline

val pipeline = new PretrainedPipeline("analyze_sentiment", lang = "en")

val result = pipeline.fullAnnotate("""Demonicus is a movie turned into a video game! I just love the story and the things that goes on in the film.It is a B-film ofcourse but that doesn`t bother one bit because its made just right and the music was rad! Horror and sword fight freaks,buy this movie now!""")

```

{:.nlu-block}
```python

import nlu
text = ["""Demonicus is a movie turned into a video game! I just love the story and the things that goes on in the film.It is a B-film ofcourse but that doesn`t bother one bit because its made just right and the music was rad! Horror and sword fight freaks,buy this movie now!"""]
result_df = nlu.load('en.classify').predict(text)
result_df

```
</div>

<div class="tabs-box" markdown="1">
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
from sparknlp.pretrained import PretrainedPipeline

pipeline = PretrainedPipeline('analyze_sentiment', lang = 'en')

result = pipeline.fullAnnotate("""Demonicus is a movie turned into a video game! I just love the story and the things that goes on in the film.It is a B-film ofcourse but that doesn`t bother one bit because its made just right and the music was rad! Horror and sword fight freaks,buy this movie now!""")
```
```scala
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline

val pipeline = new PretrainedPipeline("analyze_sentiment", lang = "en")

val result = pipeline.fullAnnotate("""Demonicus is a movie turned into a video game! I just love the story and the things that goes on in the film.It is a B-film ofcourse but that doesn`t bother one bit because its made just right and the music was rad! Horror and sword fight freaks,buy this movie now!""")
```

{:.nlu-block}
```python
import nlu
text = ["""Demonicus is a movie turned into a video game! I just love the story and the things that goes on in the film.It is a B-film ofcourse but that doesn`t bother one bit because its made just right and the music was rad! Horror and sword fight freaks,buy this movie now!"""]
result_df = nlu.load('en.classify').predict(text)
result_df
```
</div>

## Results

```bash
Results


| | text | sentiment |
|---:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------|
| 0 | Demonicus is a movie turned into a video game! I just love the story and the things that goes on in the film.It is a B-film ofcourse but that doesn`t bother one bit because its made just right and the music was rad! Horror and sword fight freaks,buy this movie now! | positive |
{:.model-param}
```

{:.model-param}
## Model Information

{:.table-model}
|---|---|
|Model Name:|analyze_sentiment|
|Type:|pipeline|
|Compatibility:|Spark NLP 4.4.2+|
|License:|Open Source|
|Edition:|Official|
|Language:|en|
|Size:|5.1 MB|

## Included Models

- DocumentAssembler
- SentenceDetector
- TokenizerModel
- NorvigSweetingModel
- ViveknSentimentModel
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---
layout: model
title: Sentiment Analysis pipeline for English (analyze_sentimentdl_glove_imdb)
author: John Snow Labs
name: analyze_sentimentdl_glove_imdb
date: 2023-05-25
tags: [open_source, english, analyze_sentimentdl_glove_imdb, pipeline, en]
task: Named Entity Recognition
language: en
edition: Spark NLP 4.4.2
spark_version: 3.4
supported: true
annotator: PipelineModel
article_header:
type: cover
use_language_switcher: "Python-Scala-Java"
---

## Description

The analyze_sentimentdl_glove_imdb is a pretrained pipeline that we can use to process text with a simple pipeline that performs basic processing steps
and recognizes entities .
It performs most of the common text processing tasks on your dataframe

## Predicted Entities



{:.btn-box}
<button class="button button-orange" disabled>Live Demo</button>
<button class="button button-orange" disabled>Open in Colab</button>
[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/analyze_sentimentdl_glove_imdb_en_4.4.2_3.4_1685051273135.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/analyze_sentimentdl_glove_imdb_en_4.4.2_3.4_1685051273135.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

## How to use

<div class="tabs-box" markdown="1">
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python

from sparknlp.pretrained import PretrainedPipelinein
pipeline = PretrainedPipeline('analyze_sentimentdl_glove_imdb', lang = 'en')
annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
annotations.keys()

```
```scala

val pipeline = new PretrainedPipeline("analyze_sentimentdl_glove_imdb", lang = "en")
val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)


```

{:.nlu-block}
```python

import nlu
text = [""Hello from John Snow Labs ! ""]
result_df = nlu.load('en.sentiment.glove').predict(text)
result_df

```
</div>

<div class="tabs-box" markdown="1">
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
from sparknlp.pretrained import PretrainedPipelinein
pipeline = PretrainedPipeline('analyze_sentimentdl_glove_imdb', lang = 'en')
annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
annotations.keys()
```
```scala
val pipeline = new PretrainedPipeline("analyze_sentimentdl_glove_imdb", lang = "en")
val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
```

{:.nlu-block}
```python
import nlu
text = [""Hello from John Snow Labs ! ""]
result_df = nlu.load('en.sentiment.glove').predict(text)
result_df
```
</div>

## Results

```bash
Results


| | document | sentence | tokens | word_embeddings | sentence_embeddings | sentiment |
|---:|:---------------------------------|:--------------------------------|:-----------------------------------------------|:-----------------------------|:-----------------------------|:------------|
| 0 | ['Hello from John Snow Labs ! '] | ['Hello from John Snow Labs !'] | ['Hello', 'from', 'John', 'Snow', 'Labs', '!'] | [[0.2668800055980682,.,...]] | [[0.0771183446049690,.,...]] | ['neg'] |


{:.model-param}
```

{:.model-param}
## Model Information

{:.table-model}
|---|---|
|Model Name:|analyze_sentimentdl_glove_imdb|
|Type:|pipeline|
|Compatibility:|Spark NLP 4.4.2+|
|License:|Open Source|
|Edition:|Official|
|Language:|en|
|Size:|161.6 MB|

## Included Models

- DocumentAssembler
- SentenceDetector
- TokenizerModel
- WordEmbeddingsModel
- SentenceEmbeddings
- SentimentDLModel
120 changes: 120 additions & 0 deletions docs/_posts/ahmedlone127/2023-05-25-check_spelling_en.md
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---
layout: model
title: Spell Checking Pipeline for English
author: John Snow Labs
name: check_spelling
date: 2023-05-25
tags: [open_source, english, check_spelling, pipeline, en]
task: Spell Check
language: en
edition: Spark NLP 4.4.2
spark_version: 3.4
supported: true
annotator: PipelineModel
article_header:
type: cover
use_language_switcher: "Python-Scala-Java"
---

## Description

The check_spelling is a pretrained pipeline that we can use to process text with a simple pipeline that performs basic processing steps
and recognizes entities .
It performs most of the common text processing tasks on your dataframe

## Predicted Entities



{:.btn-box}
<button class="button button-orange" disabled>Live Demo</button>
<button class="button button-orange" disabled>Open in Colab</button>
[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/check_spelling_en_4.4.2_3.4_1685039983204.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/check_spelling_en_4.4.2_3.4_1685039983204.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

## How to use

<div class="tabs-box" markdown="1">
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python

from sparknlp.pretrained import PretrainedPipelinein
pipeline = PretrainedPipeline('check_spelling', lang = 'en')
annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
annotations.keys()

```
```scala

val pipeline = new PretrainedPipeline("check_spelling", lang = "en")
val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)


```

{:.nlu-block}
```python

import nlu
text = [""Hello from John Snow Labs ! ""]
result_df = nlu.load('').predict(text)
result_df

```
</div>

<div class="tabs-box" markdown="1">
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
from sparknlp.pretrained import PretrainedPipelinein
pipeline = PretrainedPipeline('check_spelling', lang = 'en')
annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
annotations.keys()
```
```scala
val pipeline = new PretrainedPipeline("check_spelling", lang = "en")
val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
```

{:.nlu-block}
```python
import nlu
text = [""Hello from John Snow Labs ! ""]
result_df = nlu.load('').predict(text)
result_df
```
</div>

## Results

```bash
Results


| | document | sentence | token | checked |
|---:|:---------------------------------|:--------------------------------|:-----------------------------------------------|:-----------------------------------------------|
| 0 | ['I liek to live dangertus ! '] | ['I liek to live dangertus !'] | ['I', 'liek', 'to', 'live', 'dangertus', '!'] | ['I', 'like', 'to', 'live', 'dangerous', '!'] |


{:.model-param}
```

{:.model-param}
## Model Information

{:.table-model}
|---|---|
|Model Name:|check_spelling|
|Type:|pipeline|
|Compatibility:|Spark NLP 4.4.2+|
|License:|Open Source|
|Edition:|Official|
|Language:|en|
|Size:|906.2 KB|

## Included Models

- DocumentAssembler
- SentenceDetector
- TokenizerModel
- NorvigSweetingModel

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