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Add ZenML LLMops resource boris shared (#1589)

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@ -15,6 +15,7 @@ People are writing great tools and papers for improving outputs from GPT. Here a
- [LangChain](https://github.com/hwchase17/langchain): A popular Python/JavaScript library for chaining sequences of language model prompts.
- [LiteLLM](https://github.com/BerriAI/litellm): A minimal Python library for calling LLM APIs with a consistent format.
- [LlamaIndex](https://github.com/jerryjliu/llama_index): A Python library for augmenting LLM apps with data.
- [LLMOps Database](https://www.reddit.com/r/LocalLLaMA/comments/1h4u7au/a_nobs_database_of_how_companies_actually_deploy/): Database of how companies actually deploy LLMs in production.
- [LMQL](https://lmql.ai): A programming language for LLM interaction with support for typed prompting, control flow, constraints, and tools.
- [OpenAI Evals](https://github.com/openai/evals): An open-source library for evaluating task performance of language models and prompts.
- [Outlines](https://github.com/normal-computing/outlines): A Python library that provides a domain-specific language to simplify prompting and constrain generation.
@ -46,7 +47,6 @@ People are writing great tools and papers for improving outputs from GPT. Here a
- [Scrimba course about Assistants API](https://scrimba.com/learn/openaiassistants): A 30-minute interactive course about the Assistants API.
- [LinkedIn course: Introduction to Prompt Engineering: How to talk to the AIs](https://www.linkedin.com/learning/prompt-engineering-how-to-talk-to-the-ais/talking-to-the-ais?u=0): Short video introduction to prompt engineering
## Papers on advanced prompting to improve reasoning
- [Chain-of-Thought Prompting Elicits Reasoning in Large Language Models (2022)](https://arxiv.org/abs/2201.11903): Using few-shot prompts to ask models to think step by step improves their reasoning. PaLM's score on math word problems (GSM8K) rises from 18% to 57%.