Meet LeoLM, the first open and commercially available German Foundation Language Model built on Llama-2.
Our models extend Llama-2's capabilities into German through continued pretraining on a large corpus of German-language and mostly locality specific text.
Thanks to a compute grant at HessianAI's new supercomputer 42, we release a series foundation models trained with 8k context length
under the Llama-2 community license. Now, we're finally releasing the
leo-hessianai-70b, the largest model of this series based on
With this release, we hope to bring a new wave of opportunities to German open-source and commercial LLM research and accelerate adoption.
Read our blog post or our paper (preprint coming soon) for more details!
A project by Björn Plüster and Christoph Schuhmann in collaboration with LAION and HessianAI.
- Finetuned from: meta-llama/Llama-2-70b-hf
- Model type: Causal decoder-only transformer language model
- Language: English and German
- License: LLAMA 2 COMMUNITY LICENSE AGREEMENT
- Contact: LAION Discord or Björn Plüster
First install direct dependencies:
pip install transformers torch
Then load the model in transformers. Note that this requires lots of VRAM and most-likely multiple devices. Use
to save some memory by using a quantized version. For more quantized versions, check out our models at TheBloke's page: (coming soon!)
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained(
use_flash_attention_2=False # Set to true to use FA2. Requires `pip install flash-attn`
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