What techniques do you use to cache or pre-compute frequently generated responses to reduce model load

0 votes
Can you tell me the names of the techniques use to cache or pre-compute frequently generated responses to reduce model load?
Nov 8 in Generative AI by Ashutosh
• 8,790 points
78 views

1 answer to this question.

0 votes

Most efficient techniques to cache or pre-compute frequently generated response are as follows:

  • Response Caching
  • Memoization
  • Embeddings Caching
  • Indexing
  • Pre-Training with Fixed Responses
Note that these techniques will help in reducing model load and improving efficiency also.
answered Nov 8 by amita

Related Questions In Generative AI

0 votes
0 answers
0 votes
1 answer

What are the best practices for fine-tuning a Transformer model with custom data?

Pre-trained models can be leveraged for fine-tuning ...READ MORE

answered Nov 5 in ChatGPT by Somaya agnihotri

edited Nov 8 by Ashutosh 205 views
0 votes
1 answer

What preprocessing steps are critical for improving GAN-generated images?

Proper training data preparation is critical when ...READ MORE

answered Nov 5 in ChatGPT by anil silori

edited Nov 8 by Ashutosh 132 views
0 votes
1 answer

How do you handle bias in generative AI models during training or inference?

You can address biasness in Generative AI ...READ MORE

answered Nov 5 in Generative AI by ashirwad shrivastav

edited Nov 8 by Ashutosh 181 views
0 votes
1 answer

What methods do you use to handle out-of-vocabulary words or tokens during text generation in GPT models?

The three efficient techniques are as follows: 1.Subword Tokenization(Byte ...READ MORE

answered Nov 8 in Generative AI by ashu yadav
153 views
webinar REGISTER FOR FREE WEBINAR X
REGISTER NOW
webinar_success Thank you for registering Join Edureka Meetup community for 100+ Free Webinars each month JOIN MEETUP GROUP