This is an additional fine-tuned
flan-t5-large
model on many classification datasets.
The model supports prompt-tuned classification and is suitable for complex classification settings such as resumes classification by criteria.
You can use the model simply generating the text class name or using our
unlimited-classifier
.
The library allows to set constraints on generation and classify text into millions of classes.
How to use:
To use it with transformers library take a look into the following code snippet:
# pip install acceleratefrom transformers import T5Tokenizer, T5ForConditionalGeneration
tokenizer = T5Tokenizer.from_pretrained("knowledgator/flan-t5-large-for-classification")
model = T5ForConditionalGeneration.from_pretrained("knowledgator/flan-t5-large-for-classification", device_map="auto")
input_text = "Define sentiment of the following text: I love to travel and someday I will see the world."
input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
outputs = model.generate(input_ids)
print(tokenizer.decode(outputs[0]))
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knowledgator flan-t5-large-for-classification online free url in huggingface.co:
flan-t5-large-for-classification is an open source model from GitHub that offers a free installation service, and any user can find flan-t5-large-for-classification on GitHub to install. At the same time, huggingface.co provides the effect of flan-t5-large-for-classification install, users can directly use flan-t5-large-for-classification installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
flan-t5-large-for-classification install url in huggingface.co: