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  1. data/rnn_en-fr_split/manifest +6 -0
  2. data/rnn_en-fr_split/seq2seq_rnn-model-en-fr_1.h5 +3 -0
  3. data/rnn_en-fr_split/seq2seq_rnn-model-en-fr_2.h5 +3 -0
  4. data/rnn_en-fr_split/seq2seq_rnn-model-en-fr_3.h5 +3 -0
  5. data/rnn_en-fr_split/seq2seq_rnn-model-en-fr_4.h5 +3 -0
  6. data/rnn_en-fr_split/seq2seq_rnn-model-en-fr_5.h5 +3 -0
  7. data/rnn_fr-en_split/manifest +6 -0
  8. data/rnn_fr-en_split/seq2seq_rnn-model-fr-en_1.h5 +3 -0
  9. data/rnn_fr-en_split/seq2seq_rnn-model-fr-en_2.h5 +3 -0
  10. data/rnn_fr-en_split/seq2seq_rnn-model-fr-en_3.h5 +3 -0
  11. data/rnn_fr-en_split/seq2seq_rnn-model-fr-en_4.h5 +3 -0
  12. data/rnn_fr-en_split/seq2seq_rnn-model-fr-en_5.h5 +3 -0
  13. data/transf_en-fr_weight_split/manifest +4 -0
  14. data/transf_en-fr_weight_split/transformer-model-en-fr.weights_1.h5 +3 -0
  15. data/transf_en-fr_weight_split/transformer-model-en-fr.weights_2.h5 +3 -0
  16. data/transf_en-fr_weight_split/transformer-model-en-fr.weights_3.h5 +3 -0
  17. data/transf_fr-en_weight_split/manifest +4 -0
  18. data/transf_fr-en_weight_split/transformer-model-fr-en.weights_1.h5 +3 -0
  19. data/transf_fr-en_weight_split/transformer-model-fr-en.weights_2.h5 +3 -0
  20. data/transf_fr-en_weight_split/transformer-model-fr-en.weights_3.h5 +3 -0
  21. tabs/modelisation_seq2seq_tab.py +4 -4
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tabs/modelisation_seq2seq_tab.py CHANGED
@@ -242,8 +242,8 @@ def load_all_data():
242
  finetuned_translation_en_fr = pipeline('translation_en_to_fr', model="Demosthene-OR/t5-small-finetuned-en-to-fr")
243
  model_speech = whisper.load_model("base")
244
 
245
- merge = Merge( "https://github.com/DataScientest-Studio/Demosthene/tree/main/data/rnn_en-fr_split", dataPath, "seq2seq_rnn-model-en-fr.h5").merge(cleanup=False)
246
- merge = Merge( "https://github.com/DataScientest-Studio/Demosthene/tree/main/data/rnn_fr-en_split", dataPath, "seq2seq_rnn-model-fr-en.h5").merge(cleanup=False)
247
  rnn_en_fr = keras.models.load_model(dataPath+"/seq2seq_rnn-model-en-fr.h5", compile=False)
248
  rnn_fr_en = keras.models.load_model(dataPath+"/seq2seq_rnn-model-fr-en.h5", compile=False)
249
  rnn_en_fr.compile(optimizer="rmsprop", loss="sparse_categorical_crossentropy", metrics=["accuracy"])
@@ -254,8 +254,8 @@ def load_all_data():
254
  with keras.saving.custom_object_scope(custom_objects):
255
  transformer_en_fr = keras.models.load_model( "data/transformer-model-en-fr.h5")
256
  transformer_fr_en = keras.models.load_model( "data/transformer-model-fr-en.h5")
257
- merge = Merge( "https://github.com/DataScientest-Studio/Demosthene/tree/main/data/transf_en-fr_weight_split", "data", "transformer-model-en-fr.weights.h5").merge(cleanup=False)
258
- merge = Merge( "https://github.com/DataScientest-Studio/Demosthene/tree/main/data/transf_fr-en_weight_split", "data", "transformer-model-fr-en.weights.h5").merge(cleanup=False)
259
  else:
260
  transformer_en_fr = keras.models.load_model( dataPath+"/transformer-model-en-fr.h5", custom_objects=custom_objects )
261
  transformer_fr_en = keras.models.load_model( dataPath+"/transformer-model-fr-en.h5", custom_objects=custom_objects)
 
242
  finetuned_translation_en_fr = pipeline('translation_en_to_fr', model="Demosthene-OR/t5-small-finetuned-en-to-fr")
243
  model_speech = whisper.load_model("base")
244
 
245
+ merge = Merge( dataPath+"/rnn_en-fr_split", dataPath, "seq2seq_rnn-model-en-fr.h5").merge(cleanup=False)
246
+ merge = Merge( dataPath+"/rnn_fr-en_split", dataPath, "seq2seq_rnn-model-fr-en.h5").merge(cleanup=False)
247
  rnn_en_fr = keras.models.load_model(dataPath+"/seq2seq_rnn-model-en-fr.h5", compile=False)
248
  rnn_fr_en = keras.models.load_model(dataPath+"/seq2seq_rnn-model-fr-en.h5", compile=False)
249
  rnn_en_fr.compile(optimizer="rmsprop", loss="sparse_categorical_crossentropy", metrics=["accuracy"])
 
254
  with keras.saving.custom_object_scope(custom_objects):
255
  transformer_en_fr = keras.models.load_model( "data/transformer-model-en-fr.h5")
256
  transformer_fr_en = keras.models.load_model( "data/transformer-model-fr-en.h5")
257
+ merge = Merge( "data/transf_en-fr_weight_split", "data", "transformer-model-en-fr.weights.h5").merge(cleanup=False)
258
+ merge = Merge( "data/transf_fr-en_weight_split", "data", "transformer-model-fr-en.weights.h5").merge(cleanup=False)
259
  else:
260
  transformer_en_fr = keras.models.load_model( dataPath+"/transformer-model-en-fr.h5", custom_objects=custom_objects )
261
  transformer_fr_en = keras.models.load_model( dataPath+"/transformer-model-fr-en.h5", custom_objects=custom_objects)