HuggingFaceFW/fineweb-edu
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How to use KotshinZ/gpt2-RMT-2 with Transformers:
# Load model directly
from transformers import RecurrentMemoryTransformer
model = RecurrentMemoryTransformer.from_pretrained("KotshinZ/gpt2-RMT-2", dtype="auto")This model is a fine-tuned version of openai-community/gpt2 on the HuggingFaceFW/fineweb-edu dataset. It has been trained using TRL. For use this model. You need clone KotShinZ/Recurrent-Memory-Transformer_PreTrained.git
from transformers import pipeline
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="KotshinZ/gpt2-RMT-2", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
This model was trained with SFT. This model memory_size = 10, n_backward = 2.
Cite TRL as:
@misc{vonwerra2022trl,
title = {{TRL: Transformer Reinforcement Learning}},
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}
Base model
openai-community/gpt2
# Load model directly from transformers import RecurrentMemoryTransformer model = RecurrentMemoryTransformer.from_pretrained("KotshinZ/gpt2-RMT-2", dtype="auto")