fix

emotionMoodtag_analysis/hmv_cfg_base_stage2/model1.py

@@ -19,7 +19,7 @@ MODEL_OPTIONS = {
         "name": "DeBERTa v3 Base for Sequence Classification",
         "type": "hf_automodel_finetuned_dbt3",
         "module_path": "hmv_cfg_base_stage2.model1",
-        "hf_location": "tachygraphy-microtext-normalization-iemk/DeBERTa-v3-seqClassfication-LV2-EmotionMoodtags-Batch8",
+        "hf_location": "Tachygraphy-Microtext-Normalization-IEMK25/DeBERTa-v3-seqClassfication-LV2-EmotionMoodtags-Batch8",
         "tokenizer_class": "DebertaV2Tokenizer",
         "model_class": "DebertaV2ForSequenceClassification",
         "problem_type": "regression",

emotionMoodtag_analysis/hmv_cfg_base_stage2/model2.py

@@ -25,7 +25,7 @@ MODEL_OPTIONS = {
         "name": "DeBERTa v3 Base Custom Model with minimal Regularized Loss",
         "type": "db3_base_custom",
         "module_path": "hmv_cfg_base_stage2.model2",
-        "hf_location": "tachygraphy-microtext-normalization-iemk/DeBERTa-v3-Base-Cust-LV2-EmotionMoodtags-minRegLoss",
+        "hf_location": "Tachygraphy-Microtext-Normalization-IEMK25/DeBERTa-v3-Base-Cust-LV2-EmotionMoodtags-minRegLoss",
         "tokenizer_class": "DebertaV2Tokenizer",
         "model_class": "EmotionModel",
         "problem_type": "regression",

sentimentPolarity_analysis/hmv_cfg_base_stage1/model1.py

@@ -19,7 +19,7 @@ MODEL_OPTIONS = {
         "name": "DeBERTa v3 Base for Sequence Classification",
         "type": "hf_automodel_finetuned_dbt3",
         "module_path": "hmv_cfg_base_stage1.model1",
-        "hf_location": "tachygraphy-microtext-normalization-iemk/DeBERTa-v3-seqClassfication-LV1-SentimentPolarities-Batch8",
+        "hf_location": "Tachygraphy-Microtext-Normalization-IEMK25/DeBERTa-v3-seqClassfication-LV1-SentimentPolarities-Batch8",
         "tokenizer_class": "DebertaV2Tokenizer",
         "model_class": "DebertaV2ForSequenceClassification",
         "problem_type": "multi_label_classification",

sentimentPolarity_analysis/hmv_cfg_base_stage1/model2.py

@@ -27,7 +27,7 @@ MODEL_OPTIONS = {
         "name": "DeBERTa v3 Base Custom Model with minimal Regularized Loss",
         "type": "db3_base_custom",
         "module_path": "hmv_cfg_base_stage1.model2",
-        "hf_location": "tachygraphy-microtext-normalization-iemk/DeBERTa-v3-Base-Cust-LV1-SentimentPolarities-minRegLoss",
+        "hf_location": "Tachygraphy-Microtext-Normalization-IEMK25/DeBERTa-v3-Base-Cust-LV1-SentimentPolarities-minRegLoss",
         "tokenizer_class": "DebertaV2Tokenizer",
         "model_class": "SentimentModel",
         "problem_type": "multi_label_classification",

sentimentPolarity_analysis/hmv_cfg_base_stage1/model3.py

@@ -29,7 +29,7 @@ MODEL_OPTIONS = {
         "name": "BERT Base Uncased Custom Model",
         "type": "bert_base_uncased_custom",
         "module_path": "hmv_cfg_base_stage1.model3",
-        "hf_location": "https://huggingface.co/tachygraphy-microtext-normalization-iemk/BERT-LV1-SentimentPolarities/resolve/main/saved_weights.pt",
+        "hf_location": "https://huggingface.co/Tachygraphy-Microtext-Normalization-IEMK25/BERT-LV1-SentimentPolarities/resolve/main/saved_weights.pt",
         "tokenizer_class": "AutoTokenizer",
         "model_class": "BERT_architecture",
         "problem_type": "multi_label_classification",

sentimentPolarity_analysis/hmv_cfg_base_stage1/model4.py

@@ -37,7 +37,7 @@ MODEL_OPTIONS = {
         "name": "LSTM Custom Model",
         "type": "lstm_uncased_custom",
         "module_path": "hmv_cfg_base_stage1.model4",
-        "hf_location": "tachygraphy-microtext-normalization-iemk/LSTM-LV1-SentimentPolarities",
+        "hf_location": "Tachygraphy-Microtext-Normalization-IEMK25/LSTM-LV1-SentimentPolarities",
         "tokenizer_class": "",
         "model_class": "",
         "problem_type": "multi_label_classification",

transformation_and_Normalization/hmv_cfg_base_stage3/model1.py

@@ -17,7 +17,7 @@ MODEL_OPTIONS = {
         "name": "Facebook BART Base for Conditional Text Generation",
         "type": "hf_automodel_finetuned_fbtctg",
         "module_path": "hmv_cfg_base_stage3.model1",
-        "hf_location": "tachygraphy-microtext-normalization-iemk/BART-base-HF-Seq2Seq-Trainer-Batch4",
+        "hf_location": "Tachygraphy-Microtext-Normalization-IEMK25/BART-base-HF-Seq2Seq-Trainer-Batch4",
         "tokenizer_class": "BartTokenizer",
         "model_class": "BartForConditionalGeneration",
         "problem_type": "text_transformamtion_and_normalization",

transformation_and_Normalization/hmv_cfg_base_stage3/model2.py

@@ -17,7 +17,7 @@ MODEL_OPTIONS = {
         "name": "Microsoft Prophet Net Uncased Large for Conditional Text Generation",
         "type": "hf_automodel_finetuned_mstctg",
         "module_path": "hmv_cfg_base_stage3.model2",
-        "hf_location": "tachygraphy-microtext-normalization-iemk/ProphetNet_ForCondGen_Uncased_Large_HFTSeq2Seq_Batch4_ngram3",
+        "hf_location": "Tachygraphy-Microtext-Normalization-IEMK25/ProphetNet_ForCondGen_Uncased_Large_HFTSeq2Seq_Batch4_ngram3",
         "tokenizer_class": "ProphetNetTokenizer",
         "model_class": "ProphetNetForConditionalGeneration",
         "problem_type": "text_transformamtion_and_normalization",

transformation_and_Normalization/hmv_cfg_base_stage3/model3.py

@@ -17,7 +17,7 @@ MODEL_OPTIONS = {
         "name": "Google T5 v1.1 Base for Conditional Text Generation",
         "type": "hf_automodel_finetuned_gt5tctg",
         "module_path": "hmv_cfg_base_stage3.model3",
-        "hf_location": "tachygraphy-microtext-normalization-iemk/T5-1.1-HF-seq2seq-Trainer-Batch4",
+        "hf_location": "Tachygraphy-Microtext-Normalization-IEMK25/T5-1.1-HF-seq2seq-Trainer-Batch4",
         "tokenizer_class": "T5Tokenizer",
         "model_class": "T5ForConditionalGeneration",
         "problem_type": "text_transformamtion_and_normalization",