update app

app.py

@@ -4,25 +4,19 @@ from transformers import pipeline
 
 
 title = "CodeParrot Generator 🦜"
-description = "This is a subspace to make code generation with [CodeParrot](https://huggingface.co/lvwerra/codeparrot), it is used in a larger [space](loubnabnl/Code-generation-models-v1) for model comparison."
+description = "This is a subspace to make code generation with [CodeParrot](https://huggingface.co/lvwerra/codeparrot), it is used in a larger [space](https://huggingface.co/spaces/loubnabnl/Code-generation-models-v1) for model comparison."
 example = [
     ["def print_hello_world():", "Sample", 8, 42],
     ["def get_file_size(filepath):", "Sample", 22, 42]]
 tokenizer = AutoTokenizer.from_pretrained("lvwerra/codeparrot")
 model = AutoModelForCausalLM.from_pretrained("lvwerra/codeparrot", low_cpu_mem_usage=True)
-    
 
-def code_generation(gen_prompt, strategy, max_tokens, seed=42):
+
+def code_generation(gen_prompt, max_tokens, temperature=0.6, seed=42):
     set_seed(seed)
     gen_kwargs = {}
-    gen_kwargs["do_sample"] = strategy == "Sample"
-    gen_kwargs["max_new_tokens"] = max_tokens
-    if gen_kwargs["do_sample"]:
-        gen_kwargs["temperature"] = 0.2
-        gen_kwargs["top_k"] = 0
-        gen_kwargs["top_p"] = 0.95
     pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
-    generated_text = pipe(gen_prompt, **gen_kwargs)[0]['generated_text']
+    generated_text = pipe(gen_prompt, do_sample=True, top_p=0.95, temperature=temperature, max_new_tokens=max_tokens)[0]['generated_text']
     return generated_text
 
 
@@ -30,7 +24,6 @@ iface = gr.Interface(
     fn=code_generation, 
     inputs=[
         gr.Textbox(lines=10, label="Input code"),
-        gr.Dropdown(choices=["Greedy", "Sample"], value="Greedy"),
         gr.inputs.Slider(
             minimum=8,
             maximum=256,
@@ -38,6 +31,13 @@ iface = gr.Interface(
             default=8,
             label="Number of tokens to generate",
         ),
+        gr.inputs.Slider(
+            minimum=0,
+            maximum=2,
+            step=0.1,
+            default=0.6,
+            label="Temperature",
+        ),
         gr.inputs.Slider(
             minimum=0,
             maximum=1000,