dfsfd

app.py

@@ -19,23 +19,43 @@ before = datetime.datetime.now()
 # tokenizer = AutoTokenizer.from_pretrained("01-ai/Yi-1.5-6B-Chat")
 # model = AutoModelForCausalLM.from_pretrained("01-ai/Yi-1.5-6B-Chat")
 
-from transformers import AutoTokenizer, TFRobertaModel
-import tensorflow as tf
+# Load model directly
+from transformers import AutoTokenizer, Phi3ForCausalLM
 
-tokenizer = AutoTokenizer.from_pretrained("FacebookAI/roberta-base")
-model = TFRobertaModel.from_pretrained("FacebookAI/roberta-base")
+model = Phi3ForCausalLM.from_pretrained("microsoft/phi-3-mini-4k-instruct")
+tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-3-mini-4k-instruct")
 
-st.write('tokenizando...')
-inputs = tokenizer(question, return_tensors="tf")
+prompt = "Qual é o maior planeta do sistema solar ?"
+inputs = tokenizer(prompt, return_tensors="pt")
+
+# Generate
+generate_ids = model.generate(inputs.input_ids, max_length=30)
+output = tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
+
+st.write(output)
 
-st.write('gerando a saida...')
-outputs = model(inputs)
 
-last_hidden_states = outputs.last_hidden_state
 
-output = last_hidden_states
 
-st.write(output)
+
+
+
+
+
+# tokenizer = AutoTokenizer.from_pretrained("FacebookAI/roberta-base")
+# model = TFRobertaModel.from_pretrained("FacebookAI/roberta-base")
+
+# st.write('tokenizando...')
+# inputs = tokenizer(question, return_tensors="tf")
+
+# st.write('gerando a saida...')
+# outputs = model(inputs)
+
+# last_hidden_states = outputs.last_hidden_state
+
+# output = last_hidden_states
+
+# st.write(output)
 
 
 # st.write('tokenizando...')
@@ -118,8 +138,8 @@ print('saida gerada.')
 # answer = 'A: ' + answer
 
 print('\n\n')
-print(question)
-print(response)
+# print(question)
+# print(response)
 
 after = datetime.datetime.now()
 

requirements.txt

@@ -1,8 +1,5 @@
-keras==2.8.0
-tensorflow==2.8.0
-streamlit==1.37.1
-transformers==4.44.0
-optimum
-auto_gptq==0.5.0
+torch
+streamlit
+transformers