Actualizado Inputs

app.py

@@ -1,28 +1,17 @@
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+from transformers import pipeline
 import torch
 import gradio as gr
 
 # chatgpt-gpt4-prompts-bart-large-cnn-samsum
-tokenizer = AutoTokenizer.from_pretrained("Kaludi/chatgpt-gpt4-prompts-bart-large-cnn-samsum")
-model = AutoModelForSeq2SeqLM.from_pretrained("Kaludi/chatgpt-gpt4-prompts-bart-large-cnn-samsum", from_tf=True)
+tokenizer = AutoTokenizer.from_pretrained(
+    "Kaludi/chatgpt-gpt4-prompts-bart-large-cnn-samsum")
+model = AutoModelForSeq2SeqLM.from_pretrained(
+    "Kaludi/chatgpt-gpt4-prompts-bart-large-cnn-samsum", from_tf=True)
 
 # zephyr
-pipe = pipeline("text-generation", model="HuggingFaceH4/zephyr-7b-alpha", torch_dtype=torch.bfloat16, device_map="auto")
-
-def useZephyr(prompt):
-    messages = [
-        {
-            "role": "system",
-            "content": "You are a friendly chatbot who always responds in the style of a pirate.",
-        },
-        {"role": "user", "content": prompt},
-    ]
-    # https://huggingface.co/docs/transformers/main/en/chat_templating
-    prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
-    print(prompt)
-
-    outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
-    return outputs[0]["generated_text"]
+pipe = pipeline("text-generation", model="HuggingFaceH4/zephyr-7b-alpha",
+                torch_dtype=torch.bfloat16, device_map="auto")
 
 
 def useZephyr(prompt):
@@ -34,8 +23,11 @@ def useZephyr(prompt):
         {"role": "user", "content": prompt},
     ]
     # https://huggingface.co/docs/transformers/main/en/chat_templating
-    outputs = pipe(prompt)
+    prompt = pipe.tokenizer.apply_chat_template(
+        messages, tokenize=False, add_generation_prompt=True)
 
+    outputs = pipe(prompt, max_new_tokens=256, do_sample=True,
+                   temperature=0.7, top_k=50, top_p=0.95)
     return outputs[0]["generated_text"]
 
 
@@ -69,7 +61,8 @@ output_component = gr.Textbox(label="Output")
 examples = [["photographer"], ["developer"], ["teacher"], [
     "human resources staff"], ["recipe for ham croquettes"]]
 description = ""
-PerfectGPT = gr.Interface(useZephyr, inputs=[input_prompt, input_maxtokens], outputs=output_component,
+
+PerfectGPT = gr.Interface(generatePrompt, inputs=[input_prompt, input_maxtokens], outputs=output_component,
                           examples=examples, title="🗿 PerfectGPT v1 🗿", description=description)
 
-PerfectGPT.launch()
+PerfectGPT.launch()