📝 The LLM Cheatsheet covers the following topics: 🔰 OpenAI GPT-3: A pre-trained language model that is capable of generating human-like text, answering questions, and performing a wide range of other tasks. 🔰 Hugging Face Transformers: A library that provides pre-trained models for a wide range of natural language processing tasks, as well as tools for fine-tuning and generating text.

🔰 PyTorch: Another open source machine learning framework that is popular for natural language processing tasks. 🔰 TensorFlow: An open source machine learning framework that provides tools for building and training large language models. There are many tools and libraries available for working with large language models. This involves cleaning the text, tokenizing it into individual words or subwords, and encoding it in a format that can be fed into the model.Ģ️⃣ Fine-tuning: Large language models are often trained on large datasets, but they can also be fine-tuned on smaller, domain-specific datasets to improve their performance on specific tasks.ģ️⃣ Generation: Language models can generate text by predicting the next word in a sequence, or by sampling from a distribution of possible words.Ĥ️⃣ Translation: Language models can be used for machine translation by encoding text in one language and decoding it into another language.ĥ️⃣ Sentiment Analysis: Language models can be used for sentiment analysis by predicting the sentiment of a piece of text, such as whether it is positive, negative, or neutral. ✅ Some key concepts to understand when working with large language models include:ġ️⃣ Preprocessing: The input data must be preprocessed before training a language model. These models are designed to process natural language data and perform various tasks, including text generation, translation, sentiment analysis, and more. It covers a wide range of topics related to language modeling and provides a high-level overview of the most essential concepts and techniques in the field. The purpose of the LLM Cheatsheet is to provide a quick and easy-to-use reference guide for NLP practitioners. They use deep learning algorithms to learn patterns in the data and can generate human-like text, translate between languages, and perform a wide range of other tasks.

Large language models are a type of machine learning model that are trained on vast amounts of natural language data. It is designed to be a helpful tool for both beginners and advanced practitioners in the field of NLP. The LLM (Language Model) Cheatsheet is a quick reference guide that provides an overview of the key concepts and techniques related to natural language processing (NLP) and language modeling.

Git cheat sheet pdf in 10 mins