ahmeshaf/maven_ere_trigger_seq2seq

Base Model: google/flan-t5-large

A seq2seq event triggers tagger trained on the dataset: maven ere

Usage

Input:

triggers: I like this model and hate this sentence

Output:

like | hate

• Python

Using .generate()

from transformers import GenerationConfig, T5ForConditionalGeneration, T5Tokenizer

model_name = "ahmeshaf/maven_ere_trigger_seq2seq"

model = T5ForConditionalGeneration.from_pretrained(model_name)
tokenizer = T5Tokenizer.from_pretrained(model_name)
generation_config = GenerationConfig.from_pretrained(model_name)

tokenized_inputs = tokenizer(["I like this model and hate this sentence ."], return_tensors="pt")
outputs = model.generate(**tokenized_inputs, generation_config=generation_config)

print(tokenizer.batch_decode(outputs, skip_special_tokens=True))

# ['like | hate']

Using pipeline

from transformers import pipeline
srl = pipeline("ahmeshaf/maven_ere_trigger_seq2seq")
print(srl(["I like this model and hate this sentence ."]))

# [{'generated_text': 'like | hate'}]