Update app.py

app.py

@@ -4,6 +4,7 @@ from sklearn.feature_extraction.text import TfidfVectorizer
 from sklearn.metrics.pairwise import cosine_similarity
 from transformers import GPT2Tokenizer, GPT2LMHeadModel
 from sentence_transformers import SentenceTransformer, util
+from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
 
 import gdown
@@ -21,10 +22,12 @@ except UnicodeDecodeError:
 vectorizer = TfidfVectorizer(stop_words='english')
 X_tfidf = vectorizer.fit_transform(medical_df['Questions'])
 
-# Load pre-trained GPT-2 model and tokenizer
-model_name = "sshleifer/tiny-gpt2"
-tokenizer = GPT2Tokenizer.from_pretrained(model_name)
-model = GPT2LMHeadModel.from_pretrained(model_name)
+
+# Load TinyLlama-15M model and tokenizer
+model_name = "nickypro/tinyllama-15M"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
 
 # Load pre-trained Sentence Transformer model
 sbert_model_name = "paraphrase-MiniLM-L6-v2"