What are the features of transformers?

This recipe explains what are the features of transformers.

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Recipe Objective - What are the features of transformers?

Features:
1. Excellent results on NLU and NLG tasks
2. Educators and practitioners have a low entry hurdle.

Everyone can benefit from cutting-edge NLP:
1. Experts in deep learning
2. Practitioners who work with their hands
3. AI/ML/NLP educators and teachers


Hands-On Guide to the Art of Tuning Locality Sensitive Hashing in Python 


Reduced computing expenses and carbon footprint:
1. Researchers can share trained models rather than retraining them all the time.
2. Practitioners can save time and money by reducing compute time and costs.
3. Eight architectures, each with over 30 pre-trained models, some of which are available in over a hundred languages

Select the appropriate framework for each stage of a model's life:
1. In three lines of code, train state-of-the-art models
2. Jax, Pytorch, and TensorFlow models have deep interoperability.
3. Easily move a single model between the Jax, PyTorch, and TensorFlow frameworks.
4. Select the appropriate framework for training, evaluation, and production with ease.

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I am the Director of Data Analytics with over 10+ years of IT experience. I have a background in SQL, Python, and Big Data working with Accenture, IBM, and Infosys. I am looking to enhance my skills... Read More

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