large-language-models
Projects with this topic
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huggingface.co/transformers https://github.com/huggingface/transformers🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.Updated -
https://github.com/Lightning-AI/litgpt 20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.
🔗 https://lightning.ai/Updated -
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https://github.com/InternLM/InternLM Official release of InternLM2.5 base and chat models. 1M context support
🔗 https://internlm.intern-ai.org.cn/Updated -
💻 Decoding ML articles hub: Hands-on articles with code on production-grade MLUpdated -
https://github.com/princeton-nlp/SimPO SimPO: Simple Preference Optimization with a Reference-Free Reward
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https://github.com/InternLM/InternLM-XComposer InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output
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https://github.com/fabriziosalmi/UglyFeed Retrieve, aggregate, filter, evaluate, rewrite and serve RSS feeds using Large Language Models for fun, research and learning purposes.
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🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 11 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴 https://github.com/decodingml/llm-twin-courseUpdated -
https://github.com/YuanGongND/ltu Code, Dataset, and Pretrained Models for Audio and Speech Large Language Model "Listen, Think, and Understand".
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https://github.com/InternLM/xtuner An efficient, flexible and full-featured toolkit for fine-tuning LLM (InternLM2, Llama3, Phi3, Qwen, Mistral, ...)
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A collection of standardized JSON descriptors for Large Language Model (LLM) files.
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Official Implementation of "Graph of Thoughts: Solving Elaborate Problems with Large Language Models" https://arxiv.org/pdf/2308.09687.pdf https://github.com/spcl/graph-of-thoughts
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Language Models as Semantic Indexers
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Build, customize and control you own LLMs. From data pre-processing to fine-tuning, xTuring provides an easy way to personalize open-source LLMs. Join our discord community: https://discord.gg/TgHXuSJEk6
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Learning Multiplex Representations on Text-Attributed Graphs with One Language Model Encoder
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