Source:How to Train Long-Context Language Models (Effectively) Code:ProLong HF Page:princeton-nlp/prolong 摘要 本文研究了Language Model的继续预训练和监督微调(SFT),以有效利用长上下文信息。本文首先建立了一个可靠的评估协议来指导模型开发——本文使用了一组广泛的长上下文任务,而不是困惑度或简单的大海捞针...
I am new to LLMs and trying to figure out how to train the model with a bunch of files. I want to train the model with my files (living in a folder on my laptop) and then be able to use the model to ask questions and get answers. With OpenAI, folks have suggested using their...
I want to create a few chatbots using the Llama 3.1 8B base model, actually the company I am currently working on wants me to do it with llama. Each chatbot will be trained with a specific file and will only respond to questions related to that document. I have been researching online ...
Hi Thanks for your excellent work! Can I kindly as how long you train LlamaV-o1 and what devices you used to train? BestActivity ahmedheakl commented on Jan 13, 2025 ahmedheakl on Jan 13, 2025 Collaborator Hi @xiaobiaodu, All training stages 1,2 took 1.5 days to train on 8x...
Interacting with the models today is the art of designing a prompt rather than engineering the model architecture or training data. Dealing with LLMs can come at a cost given the expertise and resources required to build and train your models.NVIDIA NeMooffers pretrained language models that can...
The main goal is to just use their architecture but not weights. How can I do it? It seems like I can use different config initialization (e.g., LlamaConfig), but is there a more general method, of initializing the trained model and just scrambling their weight to have the same random...
They can be used to generate more creative and informative text. They can be adapted to new tasks more easily than traditional techniques. What are the challenges of using LLMs? LLMs also have some challenges, including: They require a lot of data to train. ...
Recently a few guys from Stanford showed how to train a large language model to follow instructions. They took Llama, a text-generating model from …
Specifically, we train proxy models to gauge the performance of pre-trained models, and measure the distribution deviation between a model's latent features and the task's labels, using their closeness as an indicator of model transferability. We conduct experiments on 100 widely-used opensource ...
LLaMA shares these challenges. As a foundation model, LLaMA is designed to be versatile and can be applied to many different use cases, versus a fine-tuned model that is designed for a specific task. By sharing the code for LLaMA, other researchers can more easily test new approaches to ...