MPT-7B is a decoder-style transformer pretrained from scratch on 1T tokens of English text and code. This model was trained by MosaicML and is open-sourced for commercial use (Apache-2.0).

May 5, 2023 · MPT-7B and LLaMA-7B have similar quality across all tasks, and each model scores highest (indicated in red) on 6 out of 12 tasks. Both models outperform other open source language …

May 4, 2023 · The model comprises approximately 6.7 billion parameters, organized in 32 layers with 32 attention heads per layer and a model dimension of 4096. Bias terms are omitted, and optional QK …

Jun 20, 2023 · Learn how to prepare a dataset and create a training job to fine-tune MPT-7B on Amazon SageMaker.

May 5, 2023 · Explore MosaicML Pretrained Transformer-7B (MPT 7B) including model size, context length, benchmark scores, API pricing, and licensing details. Published by MosaicML.

It's designed for reading and writing fictional stories with exceptionally long context lengths, supporting up to 65k tokens and beyond. The model has been converted to various quantization levels (4-bit, 5 …

With its impressive performance and significant parameter count, MPT rivals the quality of llama's 7 billion parameter model, making it a powerful tool for various applications.

Jun 20, 2023 · In this article, I showed how you can prepare a dataset and create a training job in SageMaker to fine-tune MPT-7B for your use case. The implementation leverages the training script …

May 18, 2023 · With nearly 7 billion parameters, MPT-7B offers impressive performance and has been trained on a diverse dataset of 1 trillion tokens, including text and code.

MPT-7B-8k: A decoder-style transformer pretrained starting from MPT-7B, but updating the sequence length to 8k and training for an additional 500B tokens, resulting in a total of 1.5T tokens of text and …