It's very cool that something sensible comes out!
Here is the "ground truth" I wrote for ~hour yesterday translating just the first few minutes into book-like format: https://
github.com/karpathy/minbp
e/blob/master/lecture.md
…
Which I think is still quite hard. I may still be useful for a few months 🙂
CODE
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Translating lecture content to book format remains challenging
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Ludwig v0.10.0 Released with Gemma, U-Net and Phi2 Support
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Announcing #Ludwig v0.10.0: Support for @Google
's #Gemma 2B / 7B Added U-Net encoder-decoder and image output feature Added #Phi2 to model presets Support for prompt lookup decoding during generation Multiple bug fixes Full release notes: https://
pbase.ai/49JwFkO -
LangSmith GA: LangGraph Examples and RAG Resources
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LangChain Release Notes, week of 2/19 LangSmith Generally Available!!
Lots of cool advanced LangGraph examples
Some great retrieval and RAG resources
Awesome community created content Read all here: https://
blog.langchain.dev/week-of-2-19-l
angchain-release-notes/
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Monte-Carlo Tree Search: UCT Algorithm for Decision-Making
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4/ Monte-Carlo Tree What? Monte-Carlo Tree Search (MCTS) is a heuristic search algorithm used in decision-making processes. In LATS, MCTS selects the best candidate using an Upper Confidence Bound for Trees (UCT).
This balances exploration and exploitation of a policy. -
LangGraph LATS Implementation Code and Video Tutorial Released
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2/ Links For those who are eager, you can check out the code and video tutorial at the links below: Youtube: https://
youtube.com/watch?t=625
Python: https://
github.com/langchain-ai/l
anggraph/blob/main/examples/lats/lats.ipynb
… Thanks to @hinthornw for the implementation. -
Code Cerebral Palsy Compassion Journey into Tech
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Today is day 1 of @fldrupalcamp
! Don't miss tomorrow's "Code, Cerebral Palsy, and Compassion: My Journey into Tech" by Matthew Ramir https://
fldrupal.camp/session/code-c
erebral-palsy-and-compassion-my-journey-tech
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Karpathy releases tokenization tutorial covering UTF-8 and byte pair encoding
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ICYMI – Andrej Karpathy has released an excellent video tutorial on "Tokenization" couple of days back. ⦿ Basics covered: Strings, Unicode code points, and encodings like UTF-8.
⦿ Byte pair encoding algorithm explained and implemented in Python.
⦿ Delving into complexities: -
Mistral and MLX for Local AI Model Deployment
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Either that or just mistral. Locally using MLX, I already did a few!
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Selenium Code Implementation Success and Out-of-Box Functionality
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That's impressive. Did the Selenium code run out of the box?
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LangSmith Improves Data Filtering for LLM Pipeline Analysis
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Better Filtering Experience in LangSmith If you’re logging a good portion of your production traces to LangSmith, you probably have a lot of data to sift through. Filtering through data in a systematic way is important for understanding how your LLM pipeline is