Update app.py

app.py

@@ -7,8 +7,7 @@ import spaces
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
 
-# !huggingface-cli login --token "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"
-HF_TOKEN = "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"
+HF_TOKEN = "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"  ##Llama Write Token
 
 MAX_MAX_NEW_TOKENS = 2048
 DEFAULT_MAX_NEW_TOKENS = 1024
@@ -31,7 +30,6 @@ if torch.cuda.is_available():
     tokenizer = AutoTokenizer.from_pretrained(model_id, use_auth_token=HF_TOKEN)
     tokenizer.use_default_system_prompt = False
 
-
 @spaces.GPU
 def generate(
     message: str,
@@ -79,13 +77,59 @@ def generate(
 
 chat_interface = gr.ChatInterface(
     fn=generate,
+    additional_inputs=[
+        gr.Textbox(label="System prompt", lines=6),
+        gr.Slider(
+            label="Max new tokens",
+            minimum=1,
+            maximum=MAX_MAX_NEW_TOKENS,
+            step=1,
+            value=DEFAULT_MAX_NEW_TOKENS,
+        ),
+        gr.Slider(
+            label="Temperature",
+            minimum=0.1,
+            maximum=4.0,
+            step=0.1,
+            value=0.6,
+        ),
+        gr.Slider(
+            label="Top-p (nucleus sampling)",
+            minimum=0.05,
+            maximum=1.0,
+            step=0.05,
+            value=0.9,
+        ),
+        gr.Slider(
+            label="Top-k",
+            minimum=1,
+            maximum=1000,
+            step=1,
+            value=50,
+        ),
+        gr.Slider(
+            label="Repetition penalty",
+            minimum=1.0,
+            maximum=2.0,
+            step=0.05,
+            value=1.2,
+        ),
+    ],
     stop_btn=None,
+    examples=[
+        ["Hello there! How are you doing?"],
+        ["Can you explain briefly to me what is the Python programming language?"],
+        ["Explain the plot of Cinderella in a sentence."],
+        ["How many hours does it take a man to eat a Helicopter?"],
+        ["Write a 100-word article on 'Benefits of Open-Source in AI research'"],
+    ],
 )
 
 with gr.Blocks(css="style.css") as demo:
     gr.Markdown(DESCRIPTION)
     gr.DuplicateButton(value="Duplicate Space for private use", elem_id="duplicate-button")
     chat_interface.render()
+    gr.Markdown(LICENSE)
 
 if __name__ == "__main__":
     demo.queue(max_size=20).launch()