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voxreality/
t5_nlu_intent_recognition

Name: t5_nlu_intent_recognition
Availability: InStock

text-generation-inference

endpoints_compatible

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A fine-tuned version of the T5 model for intent recognition. It is adept at discerning user queries, and categorizing them into requests for navigation, program details, or trade show information.

How to use:

python

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

model_path = 'voxreality/t5_nlu_intent_recognition'

tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForSeq2SeqLM.from_pretrained(model_path)

input_text = "Where is the conference room?"

input_tokenized = tokenizer.encode(input_text, return_tensors='pt')
output = model.generate(input_tokenized, max_new_tokens=100).tolist()
nlu_output_str = tokenizer.decode(output[0], skip_special_tokens=True)

print(nlu_output_str)