Predibase is the fastest, most efficient way to fine-tune and serve open-source #LLMs. ?? As the first platform designed to help #engineers productionize open-source AI, Predibase makes it easy to customize LLMs on scalable managed infra in your cloud—at a fraction of the cost of commercial LLMs. Don't believe us? Try it out for free! Fine-tune and serve Llama-2 with our two week free trial: https://pbase.ai/3SnGq2z
Predibase
软件开发
San Francisco，CA 8,079 位关注者
GPT-4 Performance at GPT-3.5 Prices: Fine-tune and Serve Small Models for Your Use Case.
关于我们
Deliver GPT-4 performance at a fraction of the cost with small models trained for your use case! As the developer platform for productionizing open-source AI, Predibase makes it easy for engineering teams to cost-efficiently fine-tune and serve small open-source LLMs on state-of-the-art infrastructure in the cloud—without sacrificing quality. Built by the team that created the internal AI platforms at Apple and Uber, Predibase is fast, efficient, and scalable for any size job. Predibase pairs an easy to use declarative interface for training models with high-end GPU capacity on serverless infra for production serving. Most importantly, Predibase is built on open-source foundations, including Ludwig and LoRAX, and can be deployed in your private cloud so all of your data and models stay in your control. In production with both Fortune 500 and high growth companies, Predibase is helping engineering teams deliver AI driven value back to their organization in days, not months. Try Predibase for free: https://predibase.com/free-trial.
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https://www.predibase.com
Predibase的外部链接
- 所属行业
- 软件开发
- 规模
- 11-50 人
- 总部
- San Francisco，CA
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- 私人持股
地点
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主要
获取路线
US，CA，San Francisco，94123
Predibase员工
动态
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?? Excited to announce that Predibase now supports fine-tuning and serving #Visual Language Models [beta]! #VLMs extend the power of traditional language models by combining visual inputs (images) with text, unlocking groundbreaking capabilities like: ?? Visual recognition and reasoning ?? Image captioning ? Visual question answering (VQA) ?? Multimodal content generation ??Image-Based Search With our new beta feature, you can: ? Easily fine-tune VLMs via the UI or SDK ? Upload image-text datasets with up to ~1,000 rows ? Deploy fine-tuned models that outperform out-of-the-box options Check out the docs here: https://pbase.ai/4g1vdgy Here’s an example of how #Meta #Llama-3.2-instruct performs out of the box vs. when fine-tuned using Predibase for a visual question answering task:
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Big things come in #small packages! Are you ready for #SmallCon! ?? Just 3 weeks away and the speaker list is absolute ?? ?? Save your spot for the first #virtual conference focused on how to unlock the full value of small models and build a modern #GenAI stack! And it's free! Check out our amazing speakers: ? Loubna Ben Allal, SmolLM Lead Hugging Face ? Daniel Hunter, Prev. the Head of AI @ Harvey AI ? Manjeet Singh, Sr. Director of AI Platforms @ Salesforce ? Lucy Park, Cofounder and CPO Upstage ? Margaret J., Head of Product @ Mistral AI ? Abhishek Patnia, Sr. Staff ML Eng @ Nubank ? Diego Guerra Orozco, GenAI Partnership Lead @ Meta ? Shreya Rajpal, CEO and Cofounder @ Guardrails AI ? Giuseppe Romagnuolo, VP of AI @ Convirza ? Atindriyo Sanyal, CTO and Cofounder @ Galileo ?? ? Maarten Van Segbroeck, Ph.D., Head of Applied Science @ Gretel ? Devvret Rishi, CEO and Cofounder @ Predibase ? Kasey Kyungsil Roh, Head of US Biz @ Upstage ? Arnav Garg, Head of ML Eng Team @ Predibase ...and more to come! Save your spot: https://lnkd.in/gDNtgY4m
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Missed Open Data Science Conference (ODSC) West last month? Arnav Garg, ML Eng Leader at Predibase, gave a talk on #finetuning fundamentals and how fine-tuning enables #GenAI teams to build smaller, faster, more accurate models. Check out the slides ??
Arnav Garg, ML Team Lead at Predibase, delivered an insightful presentation titled 'The Future is Fine-tuned: Training and Serving Task-specific LLMs' at ODSC West 2024 ?? With a proven track record in building scalable LLM capabilities like fine-tuning and inference, Arnav leads a team of engineers at Predibase focused on empowering enterprises to harness cost-effective, task-specific models. Before this, his innovative work as a Machine Learning Scientist at Atlassian included developing ML-powered smart features for Confluence and Trello, focusing on recommendation systems. His contributions to open source can be explored at github.com/arnavgarg1 ?? Want to learn how Arnav and his team are making fine-tuning Large Language Models accessible, scalable, and secure with tools like Ludwig.ai and LoRAX? ?? Explore the slide deck here: https://bit.ly/40XyYzA
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"The next frontier of innovation may lie in #smaller, more #efficient language models. This paradigm shift is already gaining momentum in the industry." We couldn't agree more Pritam Pandit! Thanks for sharing ??
Data Scientist | Machine Learning & AI Specialist | NLP & Cloud (AWS, Azure, GCP) | Python, SQL | I help making sense of Data.
Have We Hit the LLM Scaling Wall? OpenAI has been relentlessly pursuing AGI through scaling language models. Recent insights from Ilya Sutskever, co-founder and former chief scientist at OpenAI, suggest we're encountering diminishing returns from vertical scaling. The next frontier of innovation may lie in smaller, more efficient language models. This paradigm shift is already gaining momentum in the industry. ???????????????????? ???? ?????????? ???????????????? ???????????? Predibase has innovated in the small language model space, demonstrating remarkable efficiency gains. Their recent work showcases how synthetic data can match GPT-4's performance. With comparable accuracy with as few as 10 training samples. ????????-?????????????????? ???? ?????????????????????? For teams grappling with escalating GPU costs, these developments offer a promising alternative. P.S. Connect with John Trudeau for insights on optimizing your AI infrastructure costs. #SLM #GenerativeAI #Syntheticdata #Finetuning
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?? Webinar: How Convirza Analyzes Millions of Calls with Fine-Tuned SLMs ?? Curious about the latest trends in AI serving #infrastructure? Convirza’s VP of AI will share their approach: small language models (#SLMs) + multi-#LoRA serving + GPU autoscaling = more accurate models, faster analytics, lower costs, and happier customers. ?? Highlights: ?? Scale call analytics with dozens of SLMs on a single GPU ?? Slash infrastructure costs with multi-LoRA efficiency ? Sub-second insights at peak performance ?? Autoscaling GPUs to handle fluctuating capacity seamlessly Save your spot and learn how they did it: https://pbase.ai/492hUKD
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?? Sneak Peek: Continued Fine-Tuning is Coming Next Week! ?? Fine-tuning is about to get a major upgrade! ?? With our upcoming Continued Fine-Tuning feature, you can build on your existing fine-tuned adapters instead of starting from scratch. Refine performance on the same dataset or adapt to similar data—saving time and effort. This is especially valuable for large datasets, where retraining with new data could be a longer process. Now, you’ll be able to train on just the incremental additions to your dataset, leading to faster iterations. ?? What’s possible: ?? Seamless Progress: Continue training your adapter for more epochs on the same dataset. ?? Adapt to New Data: Use pre-trained adapter weights as a starting point for fine-tuning on different datasets. ?? Flexible Configurations: Add more epochs or enable early stopping while keeping other parameters intact. ?? Be among the first to try it! Let us know in the comments or DM our team for early access.
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We're in our #small model era ?? And, it's not just us. If you look at any organization seriously deploying GenAI at #scale, you'll find that they are adopting small specialized models (#SLMs) to unlock better efficiency and #accuracy. Check out our latest discussion with Marktechpost Media Inc. and Predibase CEO Devvret Rishi to get an inside look at: ? What trends we're seeing in the GenAI market, ? Why #finetuned SLMs are taking over, and ? How we're enabling that #transformation with real world customer stories. Full interview: https://lnkd.in/gRvdaAic
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?? WEBINAR ALERT ?? How Convirza Analyzes Millions of Calls Monthly with SLMs and Multi-LoRA Serving Ever wonder how a top AI platform processes massive call data without blowing up infrastructure costs? Convirza’s VP of AI is joining us live to reveal their GenAI stack for transforming call analytics at scale. Inside the webinar: ?? Convirza serves dozens of fine-tuned SLMs on the fastest multi-LoRA setup ?? Training times cut from days to hours by switching to SLMs from Longformer ?? Multi-GPU autoscaling that ensures peak performance without breaking the bank Don’t miss this dive into next-gen customer support analytics—register now! https://pbase.ai/4ev02sS
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? We're excited to announce the launch of #SmallCon: A free virtual conference for #GenAI teams looking to build big with small models! ? We're bringing together leading minds in AI from Meta Facebook, Mistral AI, Salesforce and more for deep dive tech talks and panel discussions on what it takes to build the #GenAI stack of the future and put your #SLMs into production! Our amazing list of speakers include: ? Daniel Hunter, Prev. the Head of AI @ Harvey AI ? Margaret J., Head of Product @ Mistral ? Manjeet Singh, Sr. Director of AI Platforms @ Salesforce ? Abhishek Patnia, Sr. Staff ML Eng @ Nubank ? Diego Guerra Orozco, GenAI Partnership Lead @ Meta ? Shreya Rajpal, CEO and Cofounder @ Guardrails AI ? Giuseppe Romagnuolo, Head of AI @ Convirza and much more! Check out the site for the full agenda and list of speakers: https://lnkd.in/gHh8zn9H. Make sure to save your spot! Thank you to our event cohosts Galileo ?? , Gretel and Upstage!
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