# German text generation

This is a GGUF format model converted from the canopylabs/3b-de-ft-research_release model, specifically optimized for German text processing.

LLäMmlein 7B is a German LLaMA language model with 7 billion parameters, trained from scratch on the German part of the RedPajama V2 dataset based on the adjusted Tinyllama codebase.

Wisperlama is a text generation model developed by the doctoral student team of the Wispermed group funded by the DFG, optimized based on the Llama-3.1 architecture.

This is a German Tinyllama 1B language model trained from scratch using the Tinyllama code framework and RedPajama V2 German corpus.

German language model based on Llama2 architecture, focused on German text generation tasks

A T5 model trained on the large-scale cleaned German Common Crawl corpus (GC4), specializing in German natural language processing tasks.

A BLOOM-350m language model trained from scratch on German data, a small-scale version of the BLOOM series, focused on German text generation tasks.

This is a German language model based on the GPT-2 architecture, specifically trained for German text generation tasks.

This model is trained using the WECHSEL method, achieving cross-lingual transfer of monolingual language models through efficient initialization of subword embeddings, specifically optimized for German.