So that's the general formula for how we're adding `functions` chains So far we've added: – Extraction
– Tagging
– Question-Answering with citations We're EXTREMELY open to contributions here – with this formula should be a pretty easy addition
LLMS
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Adding Function Chains: Extraction, Tagging, Question-Answering
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LLM Configuration and Prompt Templates Setup Guide
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Breaking that down: llm: this is the language model, at the moment needs to be an @OpenAI Chat model prompt: this is the prompt template to use. Generally should be a list of message templates this is pretty standard, nothing new so far
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Creating LLM Chains with LangChain Method Pattern
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Let's put it all together! We've created (with the help of @fpingham and @jxnlco
) a few chains using this method. All follow the same pattern: “`
chain = LLMChain( llm=llm, prompt=prompt, llm_kwargs=llm_kwargs, output_parser=output_parser,
)
“` -
Using Functions to Structure LLM Output Chains
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Using `functions` to structure output We're starting to add more chains that rely on functions to structure output Here's a quick overview of how we're doing that, which chains we've added so far, how to contribute, and additional resources
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US Begins Study of AI Regulation Rules for ChatGPT
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US begins study of possible rules to regulate #AI like #ChatGPT https://
reut.rs/44GpdVW #ethics -
Full Parameter Fine-tuning for Large Language Models with Limited Resources
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Full Parameter Fine-tuning for Large Language Models with Limited Resources paper page: https://
huggingface.co/papers/2306.09
782
… Large Language Models (LLMs) have revolutionized Natural Language Processing (NLP) but demand massive GPU resources for training. Lowering the threshold for LLMs -
Scaling Open-Vocabulary Object Detection with Vision-Language Models
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Scaling Open-Vocabulary Object Detection paper page: https://
huggingface.co/papers/2306.09
683
… Open-vocabulary object detection has benefited greatly from pretrained vision-language models, but is still limited by the amount of available detection training data. While detection training data can -
Block-State Transformer: Advancing State Space Models for Long Sequences
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Block-State Transformer paper page: https://
huggingface.co/papers/2306.09
539
… State space models (SSMs) have shown impressive results on tasks that require modeling long-range dependencies and efficiently scale to long sequences owing to their subquadratic runtime complexity. Originally designed -
Inverse Scaling: When Bigger Isn’t Better in Language Models
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Inverse Scaling: When Bigger Isn't Better paper page: https://
huggingface.co/papers/2306.09
479
… Work on scaling laws has found that large language models (LMs) show predictable improvements to overall loss with increased scale (model size, training data, and compute). Here, we present evidence -
Learning Julia with TidyTuesday and Tidier.jl
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Learning Julia with #TidyTuesday and Tidier.jl | Nicola Rennie https://
bit.ly/3CAFGOC #AI #MachineLearning #DeepLearning #LLMs #DataScience