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[https://medium.com/@andreasmuelder/large-language-models-for-domain-specific-language-generation-how-to-train-your-dragon-0b5360e8ed76] - - public:mzimmerm
ai, article, code, doc, generate, llm, train - 7 | id:1489780 -

training a model like Llama with 2.7 billion parameters outperformed a larger model like Vicuna with 13 billion parameters. Especially when considering resource consumption, this might be a good alternative to using a 7B Foundation model instead of a full-blown ChatGPT. The best price-to-performance base model for our use case turned out to be Mistral 7b. The model is compact enough to fit into an affordable GPU with 24GB VRAM and outperforms the other models with 7B parameters.

[https://openchat.team/] - - public:mzimmerm
ai, chat, openchat, text - 4 | id:1489776 -

Online UI to Openchat. This seems really good, open source etc. It uses the LLama2 and Mistral models, according to https://github.com/imoneoi/openchat

[https://blog.google/technology/ai/google-gemini-ai/#capabilities] - - public:mzimmerm
ai, alphacode, code, gemini, google, program, write - 7 | id:1489746 -

Advanced coding Our first version of Gemini can understand, explain and generate high-quality code in the world’s most popular programming languages, like Python, Java, C++, and Go. Using a specialized version of Gemini, we created a more advanced code generation system, AlphaCode 2,

[https://huggingface.co/blog/bert-101] - - public:mzimmerm
ai, bert, best, good, model, progress, summary, transform - 8 | id:1489741 -

Best summary of Natural Language Processing and terms - model (a language model - e.g. BertModel, defines encoder and decoder and their properties), transformer (a specific neural network based on attention paper), encoder (series of transformers on input), decoders (series of transformers on output). Bert does NOT use decoder. TensorFlow and PyTorch are possible backends to Transformers (NN). Summary: BERT is a highly complex and advanced language model that helps people automate language understanding.

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