What do you like about the model? And what should we improve?

#1
by Ihor - opened
Knowledgator Engineering org

Thank you all for your interest in our model 🤗. While it's still developing, and there are many ways to improve the model, I would like to ask what the most relevant use case for you is. What do you like, and what do we need to improve considering your request? Your feedback is really helpful for us because it allows us to focus on the really important stuff.

Thanks for the good work ! Unfortunately my use case is in italian, it would be great if it was available in other languages too

Knowledgator Engineering org

@Batchounet , thank you for your feedback! Btw we have the multilingual model. You can find it here.

It is spectacular, however I work with big data and I need to process thousands of records as fast as possible. Is there any way to apply some method of compressing the model as quantization?

Knowledgator Engineering org

@erickdp , yes, sure, you can quantize the model as regular DeBERTa. Hugging Face has a good library for that called Optimum. Please check it out here.

I have used that library several times but only for classification models, but when using it in those that are zero-shot it is impossible to use the pipeline. Maybe you know how to solve it? I leave you a screenshot running from colab.
Screenshot from 2024-03-14 19-37-09.png

Knowledgator Engineering org

The parameter of the zero-shot classification pipeline that takes labels is called candidate_labels. Also, for someone who is struggling with using a pipeline with ORTModel, you can limit the tokenizer key using the following command:

tokenizer.model_input_names = ['input_ids', 'attention_mask']

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