4. LLM app with RAG using Llama-3 running locally on your computer (100% free and without internet)
OPEN SOURCE
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ttok 0.3 releases new allow-special option for tokenization
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New release of ttok (version 0.3) adds a "–allow-special" option that fixes that: https://
github.com/simonw/ttok/re
leases/tag/0.3
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OpenAI tiktoken library rejects special tokens by default
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TIL the OpenAI tikoken library rejects text that includes special tokens by default, which affects my own "ttok" CLI tool – it raises an error if you call it like this: ttok '' –encode
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Llama-3 Memory Requirements: 5GB to 40GB Across Model Sizes
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Nope. From 5 GB for llama-3 8B to 40GB for llama-3 70B. Check it out here at @ollama
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LLMs in Space: Hardening llm.c to NASA Safety Standards
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Clearly LLMs must one day run in Space Step 1 we harden llm.c to pass the NASA code standards and style guides, certifying that the code is super safe, safe enough to run in Space. https://
en.wikipedia.org/wiki/The_Power
_of_10:_Rules_for_Developing_Safety-Critical_Code
… (see the linked PDF)
LLM training/inference in principle should be super -
Signal Defends Free Speech Record Open Source Encryption Protocol
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My record of consistently fighting for free speech and expression spans nearly 20 years. You can find and check the receipts. Further, Signal is developed in the open because we believe in verify THEN trust. Our protocol has stood the test of time, and is the gold standard across
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Llama3 Local RAG Implementation Code Guide
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Here's the code, assuming you know how to pull and run the models from Ollama. But still, if you face any issues please file a GitHub issue and I can take a look. https://
github.com/Shubhamsaboo/a
wesome-llm-apps/tree/main/llama3_local_rag
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LLaMA 3 Context Window Extended to 1 Million Tokens
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Thanks @KalleyHuang and @theinformation for writing about my work extending LLaMA 3’s context window. And shoutout to @winglian @nisten and @markatgradient who took this even further and scaled LLaMA to 1M tokens. Article in next tweet:
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Korean Translation Community Contribution to Hugging Face Hub
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Awesome to see a community contributed Korean translation of the huggingface_hub docs! Thanks to 가짜연구소 (Pseudo Lab) for your valuable contribution https://
huggingface.co/docs/huggingfa
ce_hub/main/ko/index
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Awesome LLM Apps with RAG in GitHub Repository
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Find all the awesome LLM Apps demo with RAG in the following Github Repo. P.S: Don't forget to star the repo to show your support