LoRA Ease uses AutoTrain Spacerunner to run the trainings on Hugging Face Spaces💥 https://t.co/dpFtPr8fLv
— abhishek (@abhi1thakur) 3 janvier 2024
LoRA Ease uses AutoTrain Spacerunner to run the trainings on Hugging Face Spaces
OPEN SOURCE
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LoRA Ease Utilizes AutoTrain Spacerunner for Hugging Face Training
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CommonCanvas: Copyright-Free Diffusion Model Emerges Amid OpenAI Lawsuit
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the openAI—NYT lawsuit is a big deal for copyright precedent. literally all popular models right now were trained on copyrighted data… except for one my friend from school @SkyLi0n developed a diffusion model that's not trained on any copyrighted data it's called CommonCanvas
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Groq Offers Fastest LLM Inference Speed with Llama 2 70B
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A simple post while you are easing back in after the holiday break The fastest #LLM #Inference speed is available to try right now at http://
Groq.com running #Llama 2, 70B with 4k sequence length. No "tricks" for our speed, we're an LPU™ based system. Try it out. -
GPT-Fast Adds Mixtral-8x7B Support in Efficient PyTorch
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gpt-fast now supports mixtral-8x7B, in addition to gpt/llama.
1000 lines of simple pytorch code blazing it out! https://
github.com/pytorch-labs/g
pt-fast/pull/71
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Friend launches GAN project for home GPU testing
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Exciting news from my friend and GAN co-author, I’m looking forward to trying this out on my own GPU at home
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Build Full-Stack RAG App with TypeScript Tutorial
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Build a Full-Stack RAG App with TypeScript In our newest YouTube tutorial, @BraceSproul walks through how to build a RAG app from scratch This covers prompting, API server, databases, web client application and more By the end of this video, you’ll have a complete
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Open-Source TypeScript RAG Chatbot Builder Solution
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Open-Source RAG Chatbot Builder One of the most popular use cases for GPTs is uploading it some data and creating a chatbot over that data Did you know there's an open-source solution that can do the same thing built entirely in typescript? @dialoqbase by @n4ze3m Uses
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Evaluating RAG Pipelines with LangChain and RAGAS
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Evaluating RAG pipelines using LangChain and Ragas LangChain can help you build RAG pipelines, but how do you evaluate them? We have a great integration with RAGAS to do exactly that! h/t @DataScienceHarp for writing all about it Blog: https://
deci.ai/blog/evaluatin
g-rag-pipelines-using-langchain-and-ragas/
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Building RAGs with LangChain: Practical Tutorial
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Building your own RAGs with LangChain A practical tutorial from Madhav Thacker (Senior Data Scientist @Shopify
) on how to build your own RAGs with @langchain Thanks to our friends at @arizeai for organizing! YouTube: https://
youtube.com/watch?v=IUEny5
cbys8
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LLaRA: Adapting LLMs for Dense Retrieval Tasks
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9/ Making LLMs Better at Dense Retrieval – proposes LLaRA which adapts an LLM for dense retrieval; LLaMa-2-7B was improved on benchmarks like MSMARCO and BEIR.