llama
langchain
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llama | langchain | |
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180 | 29 | |
51,530 | 80,572 | |
5.2% | 6.2% | |
8.2 | 10.0 | |
6 days ago | about 5 hours ago | |
Python | Python | |
GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
llama
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DBRX: A New Open LLM
Ironically, the LLaMA license text [1] this is lifted verbatim from is itself copyrighted [2] and doesn't grant you the permission to copy it or make changes like s/meta/dbrx/g lol.
[1] https://github.com/meta-llama/llama/blob/main/LICENSE#L65
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Markov Chains Are the Original Language Models
Predicting subsequent text is pretty much exactly what they do. Lots of very cool engineering thatβs a real feat, but at its core itβs argmax(P(token|token,corpus)):
https://github.com/facebookresearch/llama/blob/main/llama/ge...
The engineering feats are up there with anything, but itβs a next token predictor.
- Meta AI releases Code Llama 70B
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Stuff we figured out about AI in 2023
> Instead, it turns out a few hundred lines of Python is genuinely enough to train a basic version!
actually its not just a basic version. Llama 1/2's model.py is 500 lines: https://github.com/facebookresearch/llama/blob/main/llama/mo...
Mistral (is rumored to have) forked llama and is 369 lines: https://github.com/mistralai/mistral-src/blob/main/mistral/m...
and both of these are SOTA open source models.
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[D] What is a good way to maintain code readability and code quality while scaling up complexity in libraries like Hugging Face?
In transformers, they tried really hard to have a single function or method to deal with both self and cross attention mechanisms, masking, positional and relative encodings, interpolation etc. While it allows a user to use the same function/method for any model, it has led to severe parameter bloat. Just compare the original implementation of llama by FAIR with the implementation by HF to get an idea.
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Set up your own LMQL environment.
(myvenv) root@a176328806c7:/home# apt-get install git (myvenv) root@a176328806c7:/home# apt-get install wget (myvenv) root@a176328806c7:/home# git clone https://github.com/facebookresearch/llama.git (myvenv) root@a176328806c7:/home# cd llama/ (myvenv) root@a176328806c7:/home/llama# pip install -e . (myvenv) root@a176328806c7:/home/llama# ./download.sh
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Ask HN: Why the LLaMA code base is so short
I was getting into LLM and I pick up some projects. I tried to dive into the code to see what is secret sauce.
But the code is so short to the point there is nothing to really read.
https://github.com/facebookresearch/llama
I then proceed to check https://github.com/mistralai/mistral-src and suprsingly it's same.
What is exactly those codebases? It feels like just download the models.
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ExecuTorch: Enabling On-Device interference for embedded devices
Is it possible to execute a light weight language model, perhaps this https://github.com/facebookresearch/llama using ExecuTorch to run on smartphone in real time for a chatbot app ? Please share some guidance.
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Our Team's Favourite Open Source Projects Right Now
Website: https://ai.meta.com/research/publications/llama-2-open-foundation-and-fine-tuned-chat-models/ Github: https://github.com/facebookresearch/llama
- FLaNK Stack Weekly 5 September 2023
langchain
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Building a WhatsApp generative AI assistant with Amazon Bedrock and Python
Tip: Kenton Blacutt, an AWS Associate Cloud App Developer, collaborated with Langchain, creating the Amazon Dynamodb based memory class that allows us to store the history of a langchain agent in an Amazon DynamoDB.
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π Top Open Source Projects of 2023 π
LangChain was first released in October 2022 as an open-source side project, a framework that makes developing AI applications more flexible. It got so popular that it was promptly turned into a startup.
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Fuck You, Show Me the Prompt
> Furthermore, the prompt has a spelling error (Let'w) and also overly focuses on the negative about identifying errors - which makes me skeptical that this prompt has been optimized or tested.
Fixed in https://github.com/langchain-ai/langchain/commit/7c6009b76f0...
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π Local & Open Source AI: a kind ollama & LlamaIndex intro
Being able to plug third party frameworks (Langchain, LlamaIndex) so you can build complex projects
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Easy Guide to Creating Smart Chatbots with Langchain & GPT-4
Access Langchain's repository at Langchain's Repository.
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Llamafile lets you distribute and run LLMs with a single file
This comment is now a potential exploit for any such system that encounters it (in practice most won't be fooled by trivial prompt injections, but possibly more complex ones)
Here's one example I found with a quick search: https://github.com/langchain-ai/langchain/issues/5872
- Agency: Pure Go LangChain Alternative
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langchain VS agenta - a user suggested alternative
2 projects | 22 Nov 2023
- NeuralGPT - Creating The Ultimate Cooperative Multi-Agent AI Assistance Platform
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semchunk alternatives - text-splitter and langchain
3 projects | 9 Nov 2023
Owing to its complex yet highly efficient chunking algorithm, semchunk is more semantically accurate than Langchain's RecursiveCharacterTextSplitter.
What are some alternatives?
langchain - β‘ Building applications with LLMs through composability β‘ [Moved to: https://github.com/langchain-ai/langchain]
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
llama_index - LlamaIndex is a data framework for your LLM applications
chatgpt-vscode - A VSCode extension that allows you to use ChatGPT
DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
transformers - π€ Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
ollama - Get up and running with Llama 2, Mistral, Gemma, and other large language models.
gpt_index - LlamaIndex (GPT Index) is a project that provides a central interface to connect your LLM's with external data. [Moved to: https://github.com/jerryjliu/llama_index]
KoboldAI-Client
llama.cpp - LLM inference in C/C++