Ok who’s building the course on how to learn to build software with AI, GPT4 vision etc Got to be better paths than 100 days of python etc now right?
LLMS
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OpenAI Python SDK 1.0 Preview Released Breaking Changes
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We are currently previewing OpenAI Python SDK 1.0. It's a breaking change, so please try it out & give us feedback: https://
github.com/openai/openai-
python/discussions/631
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Fast REST API for Open-Source LLMs with Lower Latency
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Key features: • Easy-to-use REST API • Up to 2.9x lower latency than Replicate & 3.1x lower than Anyscale • Reliable, battle-tested infra, serving 1B tokens in our prod environment daily • One stop shop for open-source LLMs Read the API specs:
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Open-source LLM API enables fast inference without GPU requirements
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Ideal for developers seeking to incorporate open-source LLMs into their products, our API offers fast inference speeds without requiring extensive C++/CUDA knowledge or GPU access. Subscribe to Perplexity Pro to try it out: http://
pplx.ai/pro -
Perplexity Launches pplx-api LLM Platform with Mistral Llama2
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Introducing pplx-api, our LLM API which serves Mistral and Llama2 models with blazing speed and throughput. pplx-api is in public beta for our Pro subscribers! We partnered with @nvidia and @awscloud to build our proprietary inference. Learn more: https://
pplx.ai/introducing-pp
lx-api
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Hiring Data Manager for AI and Machine Learning
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Hire a data manager | Crystal Lewis https://
bit.ly/3EIJgqN
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
Are Large Language Models Developing Their Own World Models?
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Are LLMs developing their own world models, literally?@ylecun @demishassabis @drfeifei @pmddomingos @mustafasuleyman @gdb @GaryMarcus @stephen_wolfram @tegmark @chrmanning https://t.co/G7vlReC6K7
— Erik Brynjolfsson (@erikbryn) 4 octobre 2023Are LLMs developing their own world models, literally? @ylecun @demishassabis @drfeifei @pmddomingos @mustafasuleyman @gdb @GaryMarcus @stephen_wolfram @tegmark @chrmanning
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PEFT LoRA Implementation Guide for Model Fine-tuning
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Just paste it directly above your call to get_peft_model(). There's many examples around, eg: https://
github.com/huggingface/pe
ft/blob/main/examples/conditional_generation/peft_lora_seq2seq.ipynb
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PaLM 2 Excels in Multilingual QA and Mathematical Reasoning
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Curious about the capabilities of PaLM 2? In our new paper explainer, we summarize the main contributions of PaLM 2, a model that excels in various tasks like multilingual question answering and arithmetic reasoning. PaLM 2 mathematical reasoning performance surpasses SoTA (at
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BNB Quantized Layers Initialization Performance Issues
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The issue is the creation of the bnb quantised layers, not the adapters. (They are fast to init anyway since they're small.)