Update app.py

app.py

@@ -1,21 +1,21 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM, set_seed, pipeline
 
-title = "SantaCoder 🎅 Dockerfiles 🐋 Completion"
-description = "This is a subspace to make code generation with [SantaCoder fine-tuned on The Stack Dockerfiles](https://huggingface.co/mrm8488/santacoder-finetuned-the-stack-dockerfiles)"
-EXAMPLE_0 = "# Dockerfile for Express API"
+title = "SantaCoder 🎅 Swift 🍏 Completion"
+description = "This is a subspace to make code generation with [SantaCoder fine-tuned on The Stack Swift](https://huggingface.co/mrm8488/santacoder-finetuned-the-stack-swift)"
+EXAMPLE_0 = """// Swift "Hello, World!" Program"""
 
 
-CKPT = "mrm8488/santacoder-finetuned-the-stack-dockerfiles"
+CKPT = "mrm8488/santacoder-finetuned-the-stack-swift"
 
-examples = [[EXAMPLE_0, 55, 0.6, 42]]
+examples = [[EXAMPLE_0, 8, 0.6, 42]]
 tokenizer = AutoTokenizer.from_pretrained(CKPT)
-model = AutoModelForCausalLM.from_pretrained(CKPT, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(CKPT, trust_remote_code=True).to("cuda")
 
 
 def code_generation(gen_prompt, max_tokens, temperature=0.6, seed=42):
     set_seed(seed)
-    pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+    pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0)
     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