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Upload app.py
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app.py
CHANGED
@@ -16,13 +16,13 @@ try:
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except:
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print("english model load error")
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try:
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-
tokenizer_multilingual = AutoTokenizer.from_pretrained("amir22010/PyABSA_Hospital_Multilingual_allenai_tk-instruct-base-def-pos_FinedTuned_Model")
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double_multilingual_generator = AutoModelForSeq2SeqLM.from_pretrained("amir22010/PyABSA_Hospital_Multilingual_allenai_tk-instruct-base-def-pos_FinedTuned_Model")
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except:
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print("multilingual model load error")
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'''
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try:
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tokenizer_keybert = AutoTokenizer.from_pretrained("amir22010/KeyBert_ABSA_Hospital_Multilingual_allenai_tk-instruct-base-def-pos_FinedTuned_Model")
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double_keybert_generator = AutoModelForSeq2SeqLM.from_pretrained("amir22010/KeyBert_ABSA_Hospital_Multilingual_allenai_tk-instruct-base-def-pos_FinedTuned_Model")
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@@ -35,9 +35,9 @@ def perform_asde_inference(text, dataset, model_id):
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if not text:
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if model_id == "PyABSA_Hospital_English_allenai/tk-instruct-base-def-pos_FinedTuned_Model":
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df = pd.read_csv('pyabsa_english.csv')#validation dataset
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elif model_id == "PyABSA_Hospital_Multilingual_allenai/tk-instruct-base-def-pos_FinedTuned_Model":
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df = pd.read_csv('pyabsa_multilingual.csv')#validation dataset
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'''
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elif model_id == "KeyBert_ABSA_Hospital_allenai/tk-instruct-base-def-pos_FinedTuned_Model":
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df = pd.read_csv('keybert_valid.csv')#validation dataset
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'''
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@@ -67,11 +67,12 @@ def perform_asde_inference(text, dataset, model_id):
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output = double_english_generator.generate(tokenized_text.input_ids,max_length=512)
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model_generated = tokenizer_english.decode(output[0], skip_special_tokens=True)
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elif model_id == "PyABSA_Hospital_Multilingual_allenai/tk-instruct-base-def-pos_FinedTuned_Model":
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tokenized_text = tokenizer_multilingual(bos_instruction + text + delim_instruct + eos_instruct, return_tensors="pt")
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output = double_multilingual_generator.generate(tokenized_text.input_ids,max_length=512)
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model_generated = tokenizer_multilingual.decode(output[0], skip_special_tokens=True)
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-
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elif model_id == "KeyBert_ABSA_Hospital_allenai/tk-instruct-base-def-pos_FinedTuned_Model":
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tokenized_text = tokenizer_keybert(bos_instruction + text + delim_instruct + eos_instruct, return_tensors="pt")
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output = double_keybert_generator.generate(tokenized_text.input_ids,max_length=512)
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@@ -123,7 +124,7 @@ if __name__ == "__main__":
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asde_model_ids = gr.Radio(
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choices=[
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"PyABSA_Hospital_English_allenai/tk-instruct-base-def-pos_FinedTuned_Model",
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"PyABSA_Hospital_Multilingual_allenai/tk-instruct-base-def-pos_FinedTuned_Model",
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#"KeyBert_ABSA_Hospital_allenai/tk-instruct-base-def-pos_FinedTuned_Model"
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],
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value="PyABSA_Hospital_English_allenai/tk-instruct-base-def-pos_FinedTuned_Model",
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except:
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print("english model load error")
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'''
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try:
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tokenizer_multilingual = AutoTokenizer.from_pretrained("amir22010/amir22010/PyABSA_Hospital_Multilingual_allenai_tk-instruct-base-def-pos_FinedTuned_Model")
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double_multilingual_generator = AutoModelForSeq2SeqLM.from_pretrained("amir22010/PyABSA_Hospital_Multilingual_allenai_tk-instruct-base-def-pos_FinedTuned_Model")
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except:
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print("multilingual model load error")
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try:
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tokenizer_keybert = AutoTokenizer.from_pretrained("amir22010/KeyBert_ABSA_Hospital_Multilingual_allenai_tk-instruct-base-def-pos_FinedTuned_Model")
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double_keybert_generator = AutoModelForSeq2SeqLM.from_pretrained("amir22010/KeyBert_ABSA_Hospital_Multilingual_allenai_tk-instruct-base-def-pos_FinedTuned_Model")
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if not text:
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if model_id == "PyABSA_Hospital_English_allenai/tk-instruct-base-def-pos_FinedTuned_Model":
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df = pd.read_csv('pyabsa_english.csv')#validation dataset
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'''
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elif model_id == "PyABSA_Hospital_Multilingual_allenai/tk-instruct-base-def-pos_FinedTuned_Model":
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df = pd.read_csv('pyabsa_multilingual.csv')#validation dataset
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elif model_id == "KeyBert_ABSA_Hospital_allenai/tk-instruct-base-def-pos_FinedTuned_Model":
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df = pd.read_csv('keybert_valid.csv')#validation dataset
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'''
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output = double_english_generator.generate(tokenized_text.input_ids,max_length=512)
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model_generated = tokenizer_english.decode(output[0], skip_special_tokens=True)
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'''
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elif model_id == "PyABSA_Hospital_Multilingual_allenai/tk-instruct-base-def-pos_FinedTuned_Model":
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tokenized_text = tokenizer_multilingual(bos_instruction + text + delim_instruct + eos_instruct, return_tensors="pt")
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output = double_multilingual_generator.generate(tokenized_text.input_ids,max_length=512)
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model_generated = tokenizer_multilingual.decode(output[0], skip_special_tokens=True)
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+
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elif model_id == "KeyBert_ABSA_Hospital_allenai/tk-instruct-base-def-pos_FinedTuned_Model":
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tokenized_text = tokenizer_keybert(bos_instruction + text + delim_instruct + eos_instruct, return_tensors="pt")
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output = double_keybert_generator.generate(tokenized_text.input_ids,max_length=512)
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asde_model_ids = gr.Radio(
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choices=[
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"PyABSA_Hospital_English_allenai/tk-instruct-base-def-pos_FinedTuned_Model",
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#"PyABSA_Hospital_Multilingual_allenai/tk-instruct-base-def-pos_FinedTuned_Model",
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#"KeyBert_ABSA_Hospital_allenai/tk-instruct-base-def-pos_FinedTuned_Model"
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],
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value="PyABSA_Hospital_English_allenai/tk-instruct-base-def-pos_FinedTuned_Model",
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