Update utils.py

utils.py

@@ -19,7 +19,7 @@ import operator
 from typing import Annotated, Sequence, TypedDict
 import pprint
 
-from transformers import pipeline, AutoModelForSeq2SeqLM, AutoTokenizer, AutoModelForCausalLM
+from transformers import pipeline, AutoModelForSeq2SeqLM, AutoTokenizer, AutoModelForCausalLM, GPTNeoForCausalLM, GPT2Tokenizer
 from sentence_transformers import SentenceTransformer, util
 from typing import List, Dict
 
@@ -151,11 +151,16 @@ EMBEDDING_MODELL = "sentence-transformers/all-mpnet-base-v2"
 
 #Modell und Tokenizer, um die Summary über die relevanten Texte zu machen
 #mögliche Modelle: "HuggingFaceH4/zephyr-7b-alpha" #"t5-small" #"meta-llama/Meta-Llama-3-8B-Instruct" #"mistralai/Mistral-7B-Instruct-v0.3" #"microsoft/Phi-3-mini-4k-instruct" #"HuggingFaceH4/zephyr-7b-alpha" 
+HF_MODELL ="EleutherAI/gpt-neo-2.7B"
+    modell_rag = GPTNeoForCausalLM.from_pretrained(HF_MODELL)
+    tokenizer_rag = GPT2Tokenizer.from_pretrained(HF_MODELL)
+
+"""
 HF_MODELL = "microsoft/Phi-3-mini-4k-instruct"
 # Laden des Modells und Tokenizers
 modell_rag = AutoModelForCausalLM.from_pretrained(HF_MODELL)
 tokenizer_rag = AutoTokenizer.from_pretrained(HF_MODELL)
-"""
+
 HF_MODELL = "t5-small"
 modell_rag = AutoModelForSeq2SeqLM.from_pretrained(HF_MODELL)
 tokenizer_rag = AutoTokenizer.from_pretrained(HF_MODELL)