# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("aarushi-211/TOS-Longformer")
model = AutoModelForSeq2SeqLM.from_pretrained("aarushi-211/TOS-Longformer")Quick Links
Longformer fine-tuned to summarize Terms of Service
Terms of Service documents are lengthy, complex, and time-consuming to read. Due to its vague language, people often don’t understand what they are agreeing to. Hence, we have fine-tuned Longformer model to help summarize TOS and make it easy to read and understand.
This model is a fine-tuned version of allenai/led-base-16384
Dataset used: TL;DRLegal and TOS;DR website
It achieves the following results on the validation set:
- ROUGE-1: 0.28
- ROUGE-2: 0.13
- ROUGE-L: 0.27
How to Use
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("aarushi-211/TOS-Longformer")
model = AutoModelForSequenceClassification.from_pretrained("aarushi-211/TOS-Longformer")
inputs = tokenizer("Your input text here", return_tensors="pt", truncation=True)
outputs = model(**inputs)
logits = outputs.logits
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Model tree for aarushi-211/TOS-Longformer
Base model
allenai/led-base-16384
# 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="aarushi-211/TOS-Longformer")