| license: apache-2.0 | |
| library_name: transformers | |
| tags: | |
| - financial | |
| - transactions | |
| - llama | |
| - foundation-model | |
| - embeddings | |
| pipeline_tag: feature-extraction | |
| # NVIDIA Transaction Decoder Foundation Model (~29M) | |
| Pretrained checkpoint from the [NVIDIA Build Your Own Transaction Foundation Model](https://github.com/NVIDIA-AI-Blueprints/transaction-foundation-model) developer example, as described in the [NVIDIA Technical Blog](https://developer.nvidia.com/blog/build-your-own-transaction-foundation-model-for-financial-intelligence/). | |
| - Architecture: Llama decoder-only (~29M params, hidden 512, 8 layers, GQA) | |
| - Vocabulary: ~6,251 domain-specific financial transaction tokens | |
| - Trained ~3,000 steps on IBM TabFormer with NeMo AutoModel | |
| - Load with `AutoModelForCausalLM.from_pretrained(...)` and extract last-token embeddings | |
| This Hub mirror exists so Spaces / Transformers can load the Git LFS checkpoint published under `models/decoder-foundation-model/` in the upstream GitHub repo. | |