Train openllama-7b with in-context leanrning
A Reproduction of OpenLLaMA using 128 H100 GPUs in Bfloat16.
The pretrain data consists of Falcon, Starcoder, and the wikipedia, arxiv, books, stackexchange from RedPajama. In total, this encompassed nearly 1 trillion tokens.
The model was trained over a single epoch, incorporating 2000 warm-up steps and a cosine learning rate schedule, starting at 3e-5 with 4M batch size.
The sole distinction from the OpenLLaMA 7B Base lies in the organization of Falcon documents, which follows the methodology outlined in this arXiv paper.
- Downloads last month
- 1,124
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.