Hey! We can take a look if you dm us your repl URL or email us at support@replit.com
CODE
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DeepSpeed Stage 3 LoRA Bug and FSDP Migration Plans
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Theoretically, you can get it to work if you use deepspeed stage 3 with offloading. But I see there is currently a little bug for stage 3 and LoRA. I think we watned to switch from DeepSpeed to FSDP anyway though. PS: Glad you like my book!
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John Tukey Birthday: Pioneer of Software and Bit Computing
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Happy birthday to the late John Tukey, who coined the terms “software” and “bit” (short for “binary digit”). He would have turned 1101100 today: https://
nyti.ms/2X7cxr5 v/
@nytimes
, photo by Alfred Eisenstadt -
OpenAI Functions Webinar: Use Cases, Tips and Tricks
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We'll likely do our webinar next week on @OpenAI functions and the various use cases for them, and any tips and tricks Hoping to have @fpingham and @jxnlco on. Anyone else doing interesting stuff with them we should get?
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Document Tagging Schema with LangChain Framework
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Tagging Specify a schema and tag a document with those attributes As opposed to Extraction, this extracts only one instance of that schema so its more useful for classification of attributes pertaining to the text as a whole Docs: https://
python.langchain.com/en/latest/modu
les/chains/examples/tagging.html
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OpenAI Functions for Structured Data Extraction LangChain
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The new @OpenAI functions are good for other things besides agents Another killer use case is extracting structured information from unstructured docs We've adding support for extraction AND tagging in @langchain – thanks to @fpingham for code and @jxnlco for review
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Entity Extraction with LangChain: Schema-Based Data Parsing
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Extraction Specify a schema – either a dictionary or a Pydantic model – and then extract entities from a piece of text with the same schema This will return a list of objects with that schema Docs: https://
python.langchain.com/en/latest/modu
les/chains/examples/extraction.html
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Research Challenges in Software Development and Code Experimentation
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ffs, research do be a lil hard. *creates yet another branch in the main codebase to implement yet another idea*
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GPT-4 Native Tool Use Makes Building Powerful LLM Agents Easier
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This week @OpenAI gave GPT-4 the ability to use tools natively in their API. This instantly makes it easier to build powerful LLM use cases like agents with far less code than ever before. I dig into what it all means here: