Learn how Cohere is making large language models accessible and easy to use for all kinds of developers in this talk with @scale_AI
's Head of Engineering, @vjkaruna
, and Cohere's VP of Engineering, @BillMacCartney ↓
LLMS
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Making Large Language Models Accessible for Developers
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Dataset Curation Strategy for AI Use Cases
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My rule of thumb: If the use-case doesn’t have a ‘right answer’, or is creative, curate small datasets. If the use-case has a ‘right answer’, lots of data is helpful and a moat will persist for a couple of years until models are ridiculously smart. Applies often but not always
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LangChain 0.0.10: Cloud NLP, Elastic, and Model Laboratory Features
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LangChain version 0.0.10: @cloud_nlp support (
@sjwhitmore
) @elastic support (
@sjwhitmore
) support for text2text generation models on @huggingface (h/t @deliprao 4 idea) model laboratory: easily compare the same input to different models https://
github.com/hwchase17/lang
chain/
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Using LLMs to Generate Product Descriptions at Scale
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Learn how to use large language models (LLMs) to generate product descriptions for ads quickly and at scale. Get started ↓ https://
hubs.li/Q01rSBpt0 PS: This social post was generated using text summarization by Cohere. -
Democratizing Speech Technology at Lightning Speed
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Awww! Thanks, Merve!! Looking forward to democratising speech at lightning speed in the coming months <3
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New Spellbook AI Tool from Scale AI Enhances Prompt Engineering
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Just dropped: Spellbook from @scale_AI. Great ideas in here — couples prompts with uploaded training data to automatically write k-shots, give evaluation metrics for prompt variants; also lets you turn prompts to spreadsheet functions https://t.co/hNGNXmGJtV
— Riley Goodside (@goodside) 9 novembre 2022Just dropped: Spellbook from @scale_AI
. Great ideas in here — couples prompts with uploaded training data to automatically write k-shots, give evaluation metrics for prompt variants; also lets you turn prompts to spreadsheet functions -
Formal Informal Languages: Modern Prompt Engineering Approaches
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Formal Informal Languages — An interesting take on (current) prompt engineering https://
flip.it/lmLQod -
ReAct: Synergizing Reasoning and Acting in Language Models
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Learn how ReAct, a general paradigm for synergizing reasoning and acting in language models, presents more interpretable, diagnosable, and controllable task-solving trajectories while outperforming reasoning and acting only paradigms. Read the blog → https://
goo.gle/3TiNcDp -
ROME: Efficient Factual Editing in GPT Models
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MIT, Northeastern & Technion Propose ROME for Efficient Locating and Editing of Factual Associations in GPT Models
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Non-Experts Answer Expert Questions on MMLU and QuALITY
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We ask non-experts to answer expert-level questions on MMLU, and also ask people to answer questions about long QuALITY passages under a time limit that’s too short for a careful read.