LAION LeoLM 70b: Linguistically Enhanced Open Language Model
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
much anticipated leo-hessianai-70b
, the largest model of this series based on Llama-2-70b
.
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.
Model Details
- 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
Use in 🤗Transformers
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 load_in_8bit=True
or load_in_4bit=True
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
import torch
model = AutoModelForCausalLM.from_pretrained(
model="LeoLM/leo-hessianai-70b",
device_map="auto",
torch_dtype=torch.bfloat16,
use_flash_attention_2=False # Set to true to use FA2. Requires `pip install flash-attn`
)
Training parameters
Benchmarks
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