I have read the Qwen 2.5 Technical Report and other papers, but I am still curious about how they train models in two phases, with each phase using a different context length.

I have read the Qwen 2.5 Technical Report and other papers, but I am still curious about how they train models in two phases, with each phase using a different context length.

I have read the Qwen 2.5 Technical Report and other papers, but I am still curious about how they train models in two phases, with each phase using a different context length.

I’m planning to do memory fine-tune on an instruction-based model to replace a RAG and utilize proprietary data.

I am currently exploring the performance of large models in understanding knowledge in specific domains, and attempting to construct a knowledge framework similar to what humans establish when learning a subject. This understanding does not need to be flawless, but it should provide a comprehensive grasp of the core concepts and structure of the subject. […]

First why do we need to install tensorflow with cuda does it mean we dont need to install cuda globally. I installed cuda(i.e for os) globally using nvidia documentation and tensorflow cuda using pip install tensorflow[and -cuda].

I am currently working on a text2sql project. To avoid sending a large text of metadata as a part of the prompt as context, I created a set of question and answer pairs as fine tuning training data. I included all SQL metadata along with every question and the correct SQL as the answer in the training data

i want to use imagebind llm model for my task, but i can not import llama and find out the checkpoints for ImageBind-LLM.enter image description here

I have the following situation: I have a statement, e.g.

So, I’m a complete beginner on how to use any LLMs, given below is the code which I was using on my jupyter notebook to run a prompt to convert binary to decimal. However I was getting completely incorrect responses on Llama 3.