app.py

import gradio as gr
from transformers import GPT2LMHeadModel, GPT2Tokenizer
import torch

# Initialisierung des Modells und des Tokenizers
tokenizer = GPT2Tokenizer.from_pretrained("Loewolf/GPT_1.2")
model = GPT2LMHeadModel.from_pretrained("Loewolf/GPT_1.2")

def generate_text(prompt):
 input_ids = tokenizer.encode(prompt, return_tensors="pt")
 attention_mask = torch.ones(input_ids.shape, dtype=torch.long)

 max_length = model.config.n_positions if len(input_ids[0]) > model.config.n_positions else len(input_ids[0]) + 50
 beam_output = model.generate(
 input_ids,
 attention_mask=attention_mask,
 max_length=max_length,
 min_length=4,
 num_beams=5,
 no_repeat_ngram_size=2,
 early_stopping=True,
 temperature=0.7,
 top_p=0.95,
 top_k=70,
 length_penalty=2.0,
 do_sample=True,
 eos_token_id=tokenizer.eos_token_id,
 pad_token_id=tokenizer.eos_token_id 
 )
 
 text = tokenizer.decode(beam_output[0], skip_special_tokens=True)
 return text

DESCRIPTION = """\
#Löwolf GPT1 Chat

Es wird neues Löwolf GPT 1.2 verwendet.

Löwolf Chat verwendet immer das aktuelle GPT Modell von Löwolf Community!
"""
css = """
h1 {
 text-align: center;
}

#duplicate-button {
 margin: auto;
 color: white;
 background: #1565c0;
 border-radius: 100vh;
}

.contain {
 max-width: 900px;
 margin: auto;
 padding-top: 1.5rem;
}

"""

iface = gr.Interface(
 fn=generate_text,
 inputs=gr.Textbox(lines=2, placeholder="Type a message...", label="Your Message"),
 outputs=gr.Textbox(label="Löwolf Chat Responses", placeholder="Responses will appear here...", interactive=False, lines=10),
 
 css=css
)

iface.launch()