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Learn to run LLaMA-2-70B on Together AI's platform. Explore the API, playground, and documentation. Gain hands-on experience with code implementation for this powerful language model.
Explore Google's PaLM2 AI model: improvements, specialized versions, and practical applications in the Vertex AI platform. Hands-on demonstrations of various prompting techniques and code examples included.
Explore Phi 1.5, a small yet powerful language model. Learn about its development, capabilities, and potential applications through in-depth analysis and hands-on coding examples.
Explore the advancements in LLaMA2, including new base models, performance comparisons, and insights into its development and deployment on various platforms.
Explore LLaMA2 tokenizer tricks, prompt engineering techniques, and JSON conversion strategies to enhance your language model interactions and outputs.
Explore PaLM-2's integration with LangChain, covering chatbots, information retrieval, and database creation. Learn to leverage these powerful tools for advanced language processing and AI applications.
Explore multilingual fine-tuning capabilities of LLaMA2 and other language models, comparing performance and discussing implications for cross-lingual NLP tasks.
Learn to fine-tune Palm 2 models and create custom datasets for improved AI performance. Explore Vertex AI, dataset creation, and model tuning techniques.
Explore Camel project for synthetic data creation and market research using AI agents. Learn implementation techniques and practical applications through demonstrations and code examples.
Explore LangChain Output Parsers to enhance LLM results. Learn structured, comma-separated, Pydantic, fixing, and retry parsers for improved model outputs.
Enhance your AI development skills by learning to create and optimize BabyAGI using LangChain, with step-by-step code explanations and practical demonstrations.
Explore Program-aided Language Models implementation in LangChain, featuring code walkthrough, examples, and practical applications for enhanced language model performance.
Explore Flan-UL2 20B model in Google Colab using 8-bit inference. Learn about zero-shot capabilities, chain-of-thought prompting, and practical applications in various NLP tasks.
Explore LangChain's Tools and Chains: utility functions, basic chains, chaining, PAL Math, and API tools. Learn to develop applications using these powerful components.
Explore LaMini-LM: mini language models trained on diverse, large-scale instruction data. Learn about dataset creation, model training, and practical applications through paper analysis and code demonstrations.
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