404 fixes (#311)

docs/_posts/Ahmetemintek/2021-12-24-sbiobertresolve_loinc_cased_en.md

@@ -26,7 +26,7 @@ This model maps extracted clinical NER entities to LOINC codes using `sbiobert_b
 `LOINC`
 
 {:.btn-box}
-[Live Demo](https://demo.johnsnowlabs.com/healthcare/ER_LOINC_AUGMENTED/){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/24.Improved_Entity_Resolvers_in_SparkNLP_with_sBert.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_loinc_cased_en_3.3.4_2.4_1640374998947.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_loinc_cased_en_3.3.4_2.4_1640374998947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-04-02-chunkresolve_icd10pcs_clinical_en.md

@@ -26,7 +26,7 @@ Entity Resolution model Based on KNN using Word Embeddings + Word Movers Distanc
 ICD10-PCS Codes and their normalized definition with `clinical_embeddings`.
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/chunkresolve_icd10pcs_clinical_en_3.0.0_3.0_1617355415038.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/chunkresolve_icd10pcs_clinical_en_3.0.0_3.0_1617355415038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_cd_clinical_en.md

@@ -26,7 +26,7 @@ Entity Resolution model Based on KNN using Word Embeddings + Word Movers Distanc
 RxNorm Codes and their normalized definition with `clinical_embeddings`.
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/chunkresolve_rxnorm_cd_clinical_en_3.0.0_3.0_1618603400196.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/chunkresolve_rxnorm_cd_clinical_en_3.0.0_3.0_1618603400196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_sbd_clinical_en.md

@@ -26,7 +26,7 @@ Entity Resolution model Based on KNN using Word Embeddings + Word Movers Distanc
 RxNorm Codes and their normalized definition with `clinical_embeddings`.
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/chunkresolve_rxnorm_sbd_clinical_en_3.0.0_3.0_1618603306546.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/chunkresolve_rxnorm_sbd_clinical_en_3.0.0_3.0_1618603306546.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_scd_clinical_en.md

@@ -26,7 +26,7 @@ Entity Resolution model Based on KNN using Word Embeddings + Word Movers Distanc
 RxNorm Codes and their normalized definition with `clinical_embeddings`.
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/chunkresolve_rxnorm_scd_clinical_en_3.0.0_3.0_1618603397185.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/chunkresolve_rxnorm_scd_clinical_en_3.0.0_3.0_1618603397185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_xsmall_clinical_en.md

@@ -26,7 +26,7 @@ Entity Resolution model Based on KNN using Word Embeddings + Word Movers Distanc
 RxNorm Codes and their normalized definition with `clinical_embeddings`.
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/chunkresolve_rxnorm_xsmall_clinical_en_3.0.0_3.0_1618603394135.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/chunkresolve_rxnorm_xsmall_clinical_en_3.0.0_3.0_1618603394135.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_snomed_findings_clinical_en.md

@@ -26,7 +26,7 @@ Entity Resolution model Based on KNN using Word Embeddings + Word Movers Distanc
 Snomed Codes and their normalized definition with `clinical_embeddings`.
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/chunkresolve_snomed_findings_clinical_en_3.0.0_3.0_1618603404974.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/chunkresolve_snomed_findings_clinical_en_3.0.0_3.0_1618603404974.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-04-29-sbluebertresolve_loinc_en.md

@@ -26,7 +26,7 @@ Map clinical NER entities to LOINC codes.
 LOINC codes - per input NER entity
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/24.Improved_Entity_Resolvers_in_SparkNLP_with_sBert.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbluebertresolve_loinc_en_3.0.2_3.0_1619678534366.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbluebertresolve_loinc_en_3.0.2_3.0_1619678534366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_cpt_en.md

@@ -26,7 +26,7 @@ This model maps extracted medical entities to CPT codes using `sbiobert_base_cas
 Predicts CPT codes and their descriptions.
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_cpt_en_3.0.4_3.0_1621189492240.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_cpt_en_3.0.4_3.0_1621189492240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icd10cm_augmented_billable_hcc_en.md

@@ -26,7 +26,7 @@ This model maps extracted medical entities to ICD10-CM codes using `sbiobert_bas
 Outputs 7-digit billable ICD codes. In the result, look for `aux_label` parameter in the metadata to get HCC status. The HCC status can be divided to get further information: `billable status`, `hcc status`, and `hcc score`.For example, in the example shared `below the billable status is 1`, `hcc status is 1`, and `hcc score is 8`.
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_icd10cm_augmented_billable_hcc_en_3.0.4_2.4_1621189647111.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_icd10cm_augmented_billable_hcc_en_3.0.4_2.4_1621189647111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icd10cm_en.md

@@ -26,7 +26,7 @@ This model maps extracted medical entities to ICD10-CM codes using `sbiobert_bas
 Predicts ICD10-CM Codes and their normalized definitions.
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_icd10cm_en_3.0.4_3.0_1621189196513.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_icd10cm_en_3.0.4_3.0_1621189196513.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icd10pcs_en.md

@@ -26,7 +26,7 @@ This model maps extracted medical entities to ICD10-PCS codes using `sbiobert_ba
 Predicts ICD10-PCS Codes and their normalized definitions.
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_icd10pcs_en_3.0.4_3.0_1621189710474.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_icd10pcs_en_3.0.4_3.0_1621189710474.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icdo_en.md

@@ -28,7 +28,7 @@ Given an oncological entity found in the text (via NER models like ner_jsl), it
 Predicts ICD-O Codes and their normalized definition for each chunk.
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_icdo_en_3.0.4_3.0_1621191532225.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_icdo_en_3.0.4_3.0_1621191532225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_rxcui_en.md

@@ -26,7 +26,7 @@ This model maps clinical entities and concepts (like drugs/ingredients) to RxCUI
 Predicts RxCUI Codes and their normalized definition for each chunk.
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_rxcui_en_3.0.4_3.0_1621189488426.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_rxcui_en_3.0.4_3.0_1621189488426.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_auxConcepts_en.md

@@ -29,7 +29,7 @@ It has faster load time, with a speedup of about 6X when compared to previous ve
 Predicts Snomed Codes and their normalized definition for each chunk.
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_snomed_auxConcepts_en_3.0.4_3.0_1621189567327.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_snomed_auxConcepts_en_3.0.4_3.0_1621189567327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_auxConcepts_int_en.md

@@ -29,7 +29,7 @@ It has faster load time, with a speedup of about 6X when compared to previous ve
 Predicts Snomed Codes and their normalized definition for each chunk.
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_snomed_auxConcepts_int_en_3.0.4_3.0_1621191454309.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_snomed_auxConcepts_int_en_3.0.4_3.0_1621191454309.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_findings_en.md

@@ -26,7 +26,7 @@ This model maps extracted medical entities to Snomed codes (CT version) using `s
 Predicts Snomed Codes and their normalized definition for each chunk.
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_snomed_findings_en_3.0.4_3.0_1621191323188.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_snomed_findings_en_3.0.4_3.0_1621191323188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_findings_int_en.md

@@ -26,7 +26,7 @@ This model maps extracted medical entities to Snomed codes (INT version) using u
 Predicts Snomed Codes and their normalized definition for each chunk.
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_snomed_findings_int_en_3.0.4_3.0_1621189624936.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_snomed_findings_int_en_3.0.4_3.0_1621189624936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-05-21-sbertresolve_icd10cm_slim_billable_hcc_med_en.md

@@ -25,7 +25,7 @@ This model maps extracted medical entities to ICD10-CM codes using sentence embe
 Outputs 7-digit billable ICD codes. In the result, look for aux_label parameter in the metadata to get HCC status. The HCC status can be divided to get further information: billable status, hcc status, and hcc score.
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/24.Improved_Entity_Resolvers_in_SparkNLP_with_sBert.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbertresolve_icd10cm_slim_billable_hcc_med_en_3.0.4_2.4_1621590174924.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbertresolve_icd10cm_slim_billable_hcc_med_en_3.0.4_2.4_1621590174924.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}

docs/_posts/HashamUlHaq/2021-05-30-sbiobertresolve_cpt_augmented_en.md

@@ -26,7 +26,7 @@ This model maps extracted medical entities to CPT codes using `sbiobert_base_cas
 CPT codes and their descriptions.
 
 {:.btn-box}
-[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange}
+[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange}
 [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/24.Improved_Entity_Resolvers_in_SparkNLP_with_sBert.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
 [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_cpt_augmented_en_3.0.4_3.0_1622372290384.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
 [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_cpt_augmented_en_3.0.4_3.0_1622372290384.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}