metadata
license: apache-2.0
library_name: vla-foundry
tags:
- foundry
- vla_foundry
- llm
- text-generation
Foundry-LLM-1.2B-800B
A 1.2B parameter language model pretrained on 800B tokens, part of the VLA Foundry model collection.
Model Description
- Architecture: Transformer (24 layers, 2048 hidden dim, 16 heads, SwiGLU FFN, RoPE, QK-norm)
- Parameters: 1.2B (non-embedding)
- Tokenizer: SmolVLM2 (vocab size 49,280)
- Training data: 800B tokens from DCLM-Baseline-1.0
- LR schedule: Warmup + constant (no decay)
- Sequence length: 2048
Earlier checkpoint of the Foundry LLM, used as the language backbone for the downstream VLM and VLA models.
Evaluation Results
Multiple-choice reasoning benchmarks:
| HellaSwag | MMLU | ARC-e | ARC-c | PIQA | WinoGrande | OpenBookQA | BoolQ |
|---|---|---|---|---|---|---|---|
| 64.3 | 26.0 | 70.3 | 37.0 | 75.8 | 60.9 | 40.0 | 63.2 |
Usage
git clone https://github.com/TRI-ML/vla_foundry.git
cd vla_foundry
pip install -e .
from vla_foundry.models.base_model import BaseModel
model = BaseModel.from_pretrained("TRI-ML/Foundry-LLM-1.2B-800B")
Links
- Project page: tri-ml.github.io/vla_foundry
- Paper: VLA Foundry (arXiv 2604.19728)
- Code: github.com/TRI-ML/vla_foundry
- Collection: VLA Foundry collection