Added parameters for a better space

app.py

@@ -2,15 +2,15 @@ import gradio as gr
 from transformers import pipeline
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
-#tokenizer = AutoTokenizer.from_pretrained("facebook/galactica-1.3b")
-#model = AutoModelForCausalLM.from_pretrained("facebook/galactica-1.3b")
-#text2text_generator = pipeline("text-generation", model=model, tokenizer=tokenizer, num_workers=2)
+tokenizer = AutoTokenizer.from_pretrained("facebook/galactica-1.3b")
+model = AutoModelForCausalLM.from_pretrained("facebook/galactica-1.3b")
+text2text_generator = pipeline("text-generation", model=model, tokenizer=tokenizer, num_workers=2)
 
-def predict(text):
+def predict(text, max_length=64, temperature=0.7, do_sample=True):
     text = text.strip()
-    out_text = text2text_generator(text, max_length=128, 
-                              temperature=0.7, 
-                              do_sample=True,
+    out_text = text2text_generator(text, max_length=max_length, 
+                              temperature=temperature, 
+                              do_sample=do_sample,
                               eos_token_id = tokenizer.eos_token_id,
                               bos_token_id = tokenizer.bos_token_id,
                               pad_token_id = tokenizer.pad_token_id,
@@ -22,12 +22,28 @@ def predict(text):
     return out_text
 
 iface = gr.Interface.load(
-    "huggingface/facebook/galactica-1.3b",
-    #fn=predict, 
-    #inputs=gr.Textbox(lines=10),
-    #outputs=gr.HTML(),
-    description="Galactica",
-    examples=[["The attention mechanism in LLM is"]]
+    fn=predict, 
+    inputs=[
+        gr.inputs.Textbox(lines=5, label="Input Text"),
+        gr.inputs.Slider(minimum=32, maximum=256, default=64, label="Max Length"),
+        gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.7, step=0.1, label="Temperature"),
+        gr.inputs.Checkbox(label="Do Sample"),
+    ],
+    outputs=gr.HTML(),
+    description="Galactica Base Model",
+    examples=[[
+            "The attention mechanism in LLM is",
+            128,
+            0.7,
+            True
+        ], 
+        [
+            "Title: Attention is all you need\n\nAbstract:",
+            128,
+            0.7,
+            True
+        ]
+    ]
 )
 
 iface.launch()