google

app.py

@@ -3,9 +3,31 @@ from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
 # Supported summarization models
 model_choices = {
+    # 🥇 High Accuracy Models
     "Pegasus (google/pegasus-xsum)": "google/pegasus-xsum",
-    "BART (facebook/bart-large-cnn)": "facebook/bart-large-cnn",
-    "T5 (t5-small)": "t5-small"
+    "BigBird-Pegasus (google/bigbird-pegasus-large-arxiv)": "google/bigbird-pegasus-large-arxiv",
+    "LongT5 Large (google/long-t5-tglobal-large)": "google/long-t5-tglobal-large",
+    "BART Large CNN (facebook/bart-large-cnn)": "facebook/bart-large-cnn",
+    "ProphetNet (microsoft/prophetnet-large-uncased-cnndm)": "microsoft/prophetnet-large-uncased-cnndm",
+    "LED (allenai/led-base-16384)": "allenai/led-base-16384",
+    "T5 Large (t5-large)": "t5-large",
+    "Flan-T5 Large (google/flan-t5-large)": "google/flan-t5-large",
+
+    # ⚖️ Balanced (Speed vs Accuracy)
+    "DistilBART CNN (sshleifer/distilbart-cnn-12-6)": "sshleifer/distilbart-cnn-12-6",
+    "DistilBART XSum (mrm8488/distilbart-xsum-12-6)": "mrm8488/distilbart-xsum-12-6",
+    "T5 Base (t5-base)": "t5-base",
+    "Flan-T5 Base (google/flan-t5-base)": "google/flan-t5-base",
+    "BART CNN SamSum (philschmid/bart-large-cnn-samsum)": "philschmid/bart-large-cnn-samsum",
+    "T5 SamSum (knkarthick/pegasus-samsum)": "knkarthick/pegasus-samsum",
+    "LongT5 Base (google/long-t5-tglobal-base)": "google/long-t5-tglobal-base",
+
+    # ⚡ Lighter / Faster Models
+    "T5 Small (t5-small)": "t5-small",
+    "MBART (facebook/mbart-large-cc25)": "facebook/mbart-large-cc25",
+    "MarianMT (Helsinki-NLP/opus-mt-en-ro)": "Helsinki-NLP/opus-mt-en-ro",  # not trained for summarization, just as placeholder
+    "Falcon Instruct (tiiuae/falcon-7b-instruct)": "tiiuae/falcon-7b-instruct",  # general-purpose, not summarization-specific
+    "BART ELI5 (yjernite/bart_eli5)": "yjernite/bart_eli5"  # trained for explain-like-I'm-5
 }
 
 # Cache for loaded models/tokenizers