using zephyr model

app.py

@@ -46,8 +46,8 @@ h1 {
 """
 
 # Load the tokenizer and model
-tokenizer = AutoTokenizer.from_pretrained("cognitivecomputations/dolphin-2.9-llama3-8b")
-model = AutoModelForCausalLM.from_pretrained("cognitivecomputations/dolphin-2.9-llama3-8b", device_map="auto")  # to("cuda:0") 
+tokenizer = AutoTokenizer.from_pretrained("HuggingFaceH4/zephyr-7b-beta")
+model = AutoModelForCausalLM.from_pretrained("HuggingFaceH4/zephyr-7b-beta", device_map="auto")  # to("cuda:0") 
 terminators = [
     tokenizer.eos_token_id,
     tokenizer.convert_tokens_to_ids("<|eot_id|>")