RDPDLM / app.py
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import gradio as gr
from transformers import AutoModelForCausalLM,AutoModel
from transformers import AutoTokenizer
import torch
model = AutoModel.from_pretrained("aframson/RDPDLM",trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained("aframson/RDPDLM",trust_remote_code=True)
def Generate(context):
context_tokens = torch.tensor(tokenizer._encode(context), dtype=torch.long).unsqueeze(0) # Encode the text
# Generate text based on the context
generated_text = model.generate(context_tokens, max_new_tokens=10)[0].tolist()
return tokenizer._decode(generated_text)
iface = gr.Interface(fn=Generate, inputs="text", outputs="text")
iface.launch()