A language model predicts the next word in the sequence based on the specific words that have come before it in the sequence. It is also possible to develop language models at the character level using neural networks. The benefit of character-based language models is their small vocabulary and flexibility in handling any words, punctuation, […]
Search results for "language models"
Datasets for Natural Language Processing
You need datasets to practice on when getting started with deep learning for natural language processing tasks. It is better to use small datasets that you can download quickly and do not take too long to fit models. Further, it is also helpful to use standard datasets that are well understood and widely used so […]
Promise of Deep Learning for Natural Language Processing
The promise of deep learning in the field of natural language processing is the better performance by models that may require more data but less linguistic expertise to train and operate. There is a lot of hype and large claims around deep learning methods, but beyond the hype, deep learning methods are achieving state-of-the-art results on […]
What Is Natural Language Processing?
Natural Language Processing, or NLP for short, is broadly defined as the automatic manipulation of natural language, like speech and text, by software. The study of natural language processing has been around for more than 50 years and grew out of the field of linguistics with the rise of computers. In this post, you will […]
7 Applications of Deep Learning for Natural Language Processing
The field of natural language processing is shifting from statistical methods to neural network methods. There are still many challenging problems to solve in natural language. Nevertheless, deep learning methods are achieving state-of-the-art results on some specific language problems. It is not just the performance of deep learning models on benchmark problems that is most […]
Oxford Course on Deep Learning for Natural Language Processing
Deep Learning methods achieve state-of-the-art results on a suite of natural language processing problems What makes this exciting is that single models are trained end-to-end, replacing a suite of specialized statistical models. The University of Oxford in the UK teaches a course on Deep Learning for Natural Language Processing and much of the materials for […]
Review of Stanford Course on Deep Learning for Natural Language Processing
Natural Language Processing, or NLP, is a subfield of machine learning concerned with understanding speech and text data. Statistical methods and statistical machine learning dominate the field and more recently deep learning methods have proven very effective in challenging NLP problems like speech recognition and text translation. In this post, you will discover the Stanford […]
Top Books on Natural Language Processing
Natural Language Processing, or NLP for short, is the study of computational methods for working with speech and text data. The field is dominated by the statistical paradigm and machine learning methods are used for developing predictive models. In this post, you will discover the top books that you can read to get started with […]
Using LoRA in Stable Diffusion
The deep learning model of Stable Diffusion is huge. The weight file is multiple GB large. Retraining the model means to update a lot of weights and that is a lot of work. Sometimes we must modify the Stable Diffusion model, for example, to define a new interpretation of prompts or make the model to […]
Fast and Cheap Fine-Tuned LLM Inference with LoRA Exchange (LoRAX)
Sponsored Content By Travis Addair & Geoffrey Angus If you’d like to learn more about how to efficiently and cost-effectively fine-tune and serve open-source LLMs with LoRAX, join our November 7th webinar. Developers are realizing that smaller, specialized language models such as LLaMA-2-7b outperform larger general-purpose models like GPT-4 when fine-tuned with proprietary […]