NortheasternUniversity/big_patent
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How to use pszemraj/long-t5-tglobal-base-16384-booksum-V11-big_patent-V2 with Transformers:
# Use a pipeline as a high-level helper
# Warning: Pipeline type "summarization" is no longer supported in transformers v5.
# You must load the model directly (see below) or downgrade to v4.x with:
# 'pip install "transformers<5.0.0'
from transformers import pipeline
pipe = pipeline("summarization", model="pszemraj/long-t5-tglobal-base-16384-booksum-V11-big_patent-V2") # Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("pszemraj/long-t5-tglobal-base-16384-booksum-V11-big_patent-V2")
model = AutoModelForSeq2SeqLM.from_pretrained("pszemraj/long-t5-tglobal-base-16384-booksum-V11-big_patent-V2")An experiment testing some transfer learning with pszemraj/long-t5-tglobal-base-16384-book-summary to evaluate the ability to learn some technical documentation through the big_patent dataset on huggingface.
This checkpoint has been trained on dataset subsection y of big_patent for approx 400 steps of functional batch size 128.