PRV-AI-2.0

An independent text-to-text generation model developed by Prava1, architecturally congruent with the encoder-decoder transformer paradigm that has been explored in contemporary sequence-to-sequence research.

Model Details

• Model Name: PRV-AI-2.0
• Author: Prava1
• License: Apache 2.0
• Architecture: Encoder-Decoder Transformer (T5-class)

Usage

from transformers import T5ForConditionalGeneration, T5Tokenizer

tokenizer = T5Tokenizer.from_pretrained("Prava1/PRV-AI-2.0")
model = T5ForConditionalGeneration.from_pretrained("Prava1/PRV-AI-2.0")

inputs = tokenizer("Summarize: AI is transforming the world.", return_tensors="pt")
outputs = model.generate(**inputs)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Acknowledgements

The foundational breakthroughs in instruction-tuned sequence transduction, as explored in prior large-scale multilingual pretraining literature, have been instrumentally consequential to advancements in this domain.