Spaces:
Sleeping
Sleeping
File size: 1,444 Bytes
26532db c2c3e4f 07099e3 c2c3e4f 07099e3 c2c3e4f 07099e3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 |
import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer
import random
from datetime import datetime
from PyPDF2 import PdfReader
import json
from transformers import AutoModelForCausalLM, AutoTokenizer
# Replace 'username/your_model_name' with your Hugging Face model name
model_name = "username/your_model_name"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
def generate_tweet(prompt):
# Tokenize the input
inputs = tokenizer(prompt, return_tensors="pt")
# Generate text using the model
outputs = model.generate(
inputs["input_ids"],
max_length=280, # Limit tweets to 280 characters
num_return_sequences=1, # Number of tweets to generate
top_k=50, # Sampling from top k tokens
top_p=0.95, # Sampling from top p cumulative probability
temperature=0.7, # Adjust creativity
do_sample=True, # Enable sampling
)
# Decode the generated text
tweet = tokenizer.decode(outputs[0], skip_special_tokens=True)
return tweet
interface = gr.Interface(
fn=generate_tweet, # The function to call
inputs="text", # User input is a single text box
outputs="text", # Output is text
title="AI Tweet Generator",
description="Enter a topic or a few words, and the AI will generate a creative tweet!"
)
# Launch the app
interface.launch()
|