Spaces:
Running
Running
File size: 1,464 Bytes
d09118e 45ce02f d09118e fb4cd02 45ce02f fb4cd02 45ce02f fb4cd02 45ce02f fb4cd02 45ce02f fb4cd02 45ce02f fb4cd02 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 |
---
title: README
emoji: π
colorFrom: indigo
colorTo: blue
sdk: static
pinned: false
---
# IBM AI Platform
IBM's AI Platform is a collection of components developed out of IBM Research used for development, inference, training, and tuning of foundation models leveraging PyTorch native components.
## Optimizations
In this platform, we aim to bring the latest optimizations for pre-training/inference/fine-tuning to all of our models. A few of these optimizations include, but are not limited to:
- fully compilable models with no graph breaks
- full tensor-parallel support for all applicable modules developed in fms
- training scripts leveraging FSDP
- state of the art light-weight speculators for improving inference performance
## Usage
Components such as speculative decoding have been deployed to [vLLM](https://docs.vllm.ai/en/latest/getting_started/examples/mlpspeculator.html)
## Repositories
- [foundation-model-stack](https://github.com/foundation-model-stack/foundation-model-stack): Main repository for which all AI platform models are based
- [fms-extras](https://github.com/foundation-model-stack/fms-extras): New features staged to be integrated with our AI platform
- [fms-fsdp](https://github.com/foundation-model-stack/fms-fsdp): Pre-Training Examples using FSDP wrapped foundation models
- [fms-hf-tuning](https://github.com/foundation-model-stack/fms-hf-tuning): Basic Tuning scripts for AI platform models leveraging SFTTrainer |