LLM_MODEL datificate/gpt2-small-swedish

app.py

@@ -11,11 +11,11 @@ from langchain.text_splitter import RecursiveCharacterTextSplitter
 DOCS_DIR       = "document"
 INDEX_DIR      = "faiss_index"
 EMB_MODEL      = "KBLab/sentence-bert-swedish-cased"
-#LLM_MODEL      = "tiiuae/falcon-rw-1b"
-#LLM_MODEL      = "google/flan-t5-base"
-#LLM_MODEL      = "bigscience/bloom-560m"
-LLM_MODEL      = "NbAiLab/nb-gpt-j-6B"
-
+#LLM_MODEL      = "tiiuae/falcon-rw-1b" # Dålig
+#LLM_MODEL      = "google/flan-t5-base" # Dålig
+#LLM_MODEL      = "bigscience/bloom-560m" # Dålig
+#LLM_MODEL      = "NbAiLab/nb-gpt-j-6B" #- Restricted 
+LLM_MODEL      = "datificate/gpt2-small-swedish"
 
 CHUNK_SIZE     = 400
 CHUNK_OVERLAP  = 40
@@ -115,6 +115,7 @@ def chat_fn(q, temp, history):
 with gr.Blocks() as demo:
     gr.Markdown("# 📚 Svensk RAG‑chat")
     gr.Markdown(f"**PDF‑filer:** {', '.join(os.listdir(DOCS_DIR)) or '–'}")
+    gr.Markdown(f"**LLM-modell som används:** `{LLM_MODEL}`", elem_id="llm-info")
 
     with gr.Row():
         q_test = gr.Textbox(label="🔎 Test Retrieval")