There really is no reason anyone should be using free ChatGPT-3.5 anymore. Not only can you still get GPT-4 access for free through Microsoft Copilot (in creative mode), but if you want a GPT-3.5 class model, Llama 3 is much better & free (for now), here: https://
meta.ai
LLMS
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Free GPT-4 and Llama 3 alternatives to ChatGPT
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Open Models Drive Rapid AI Capability Improvements and Speed
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Because anyone can work with them, open models are likely to improve very quickly, creating a lot of capabilities focused on factors ranging from speed to costs.
— Ethan Mollick (@emollick) 19 avril 2024
Here is the new Llama 3 70B being served by Groq (with a q) at 224 tokens/second. This is real-time of me using it. pic.twitter.com/L6i6T6OBbWBecause anyone can work with them, open models are likely to improve very quickly, creating a lot of capabilities focused on factors ranging from speed to costs. Here is the new Llama 3 70B being served by Groq (with a q) at 224 tokens/second. This is real-time of me using it.
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LangChain Weekly Release: Evaluations, Tool Calling, Monitoring
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LangChain Release Notes, week of 4/15 Evaluations video series Standardized tool calling in LangChain Production monitoring and automations in LangSmith New RAG From Scratch videos
Community created content! Read it all here: https://
blog.langchain.dev/week-of-4-15-l
angchain-release-notes/
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Fine-tuning vs RAG: When to Use Each Approach
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That's not the same as believing that fine tuning can't teach a model new knowledge under any circumstances – but in practice many people I see who think they need to fine tune a model would be better off using RAG instead
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RAG vs Fine-tuning for Small Document Loading
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My understanding is that if you want to eg load your company employee handbook (~20 page PDF) into a model you're likely to get much better results with RAG than with fine-tuning – can you fine tune such that the model reliable answers questions about something that small?
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Open-Source Model Beats Claude 3 Opus at 300 Tokens Per Second
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We now have an open-source model that is beating Claude 3 Opus…
— Matt Shumer (@mattshumer_) 19 avril 2024
being served at nearly **300 tokens per second** on @GroqInc.
The applications built off of this tech will be nothing short of revolutionary. pic.twitter.com/v934g0rwU5We now have an open-source model that is beating Claude 3 Opus… being served at nearly **300 tokens per second** on @GroqInc
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Groq Serves LLaMA 3 at Record 800 Tokens Per Second
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My mind is blown.@GroqInc is serving LLaMA 3 at over 800 tokens per second!
— Matt Shumer (@mattshumer_) 19 avril 2024
800. Tokens. Per. Second.
This unlocks so many incredible use-cases.
It's one thing to see my demo — it's another thing entirely to experience it for yourself.
Do yourself a favor and try it asap. pic.twitter.com/Rd5NW5SDlWMy mind is blown. @GroqInc is serving LLaMA 3 at over 800 tokens per second! 800. Tokens. Per. Second. This unlocks so many incredible use-cases. It's one thing to see my demo — it's another thing entirely to experience it for yourself. Do yourself a favor and try it asap.
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Breaking Down the Wildest AI News Week
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We've just experienced the craziest week in #ArtificialIntelligence in the past year. ChatGPT, GPT-4 Turbo, Mixtral 8x22b, Llama 3… I break down all the latest AI news in my newest video → https://youtu.be/fO4RwiNSeuE
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Building Reliable Local RAG Agents with Llama3
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Reliable, fully local RAG agents with Llama3 With the release of Llama3, there's high interest in agents that run reliably & locally (e.g., on your laptop). Here, we show to how build reliable local agents using LangGraph and Llama3-8b from scratch. As a example, we combine
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Opus Brief Reign Ends as Llama-3-400B Emerges as GPT-5 Contender
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Opus only lasted like 2 weeks at the top RIP Llama-3-400B finna be gpt 5 level i think these guys may have overshot lmao