Thanks Bing AI

app.py

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+from transformers import AutoTokenizer, AutoModelForMaskedLM
+import torch
+
+# Load the model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained("jfernandez/cebfil-roberta")
+model = AutoModelForMaskedLM.from_pretrained("jfernandez/cebfil-roberta")
+
+# Define a function to generate responses
+def generate_response(text):
+  # Add a mask token at the end of the text
+  text = text + " <mask>"
+  # Tokenize the text and get the input ids
+  inputs = tokenizer(text, return_tensors="pt")
+  input_ids = inputs["input_ids"]
+  # Get the logits from the model
+  outputs = model(**inputs)
+  logits = outputs.logits
+  # Get the most likely token id for the mask
+  mask_token_id = tokenizer.mask_token_id
+  mask_token_index = torch.where(input_ids == mask_token_id)[1]
+  token_logits = logits[0, mask_token_index, :]
+  top_5_tokens = torch.topk(token_logits, k=5).indices # get top 5 tokens
+  predicted_tokens = tokenizer.convert_ids_to_tokens(top_5_tokens) # convert ids to tokens
+  
+  # Choose one of the predicted tokens randomly and replace the mask with it
+  import random
+  response_token = random.choice(predicted_tokens)
+  response_text = text.replace("<mask>", response_token)
+  
+  return response_text
+
+# Test the function with some examples
+print(generate_response("Komosta ka"))
+print(generate_response("Unsa imong pangalan"))
+print(generate_response("Salamat sa"))