Poland is making significant strides in the field of language processing with the development of the Bielik 7B v0.1, a Polish language model with 7 billion parameters. Created by a collaborative effort between the open-science project SpeakLeash and the High Performance Computing center ACK Cyfronet AGH, this model leverages a vast corpus of Polish texts and employs advanced machine learning techniques to enhance linguistic applications in the Polish language.
Bielik 7B v0.1 builds upon the architecture of the Mistral 7B v0.1 model, incorporating innovations like the SwiGLU activation function, Rotary Positional Embeddings, and Root Mean Square Layer Normalization. These enhancements not only enable the handling of long sequence data more efficiently but also improve the model’s performance significantly. For instance, it achieved a 9 percentage point increase in average score on the RAG Reader task compared to its predecessor.
A key aspect of Bielik 7B v0.1’s development was the adaptation of an existing model to handle the nuances of the Polish language, a challenge given the linguistic and semantic differences from English. The training process involved meticulous data preparation and evaluation, ensuring that the model learned from high-quality and diverse Polish texts. This involved removing unwanted text fragments, anonymizing personal data, and fixing encoding issues.
The model’s tokenizer was also refined to better accommodate Polish linguistic features, enhancing its efficiency and effectiveness in text generation. Comparisons of tokenization processes showed improvements in the number of tokens generated, which translates to faster and more efficient text processing.
Evaluations on new frameworks like the Open PL LLM Leaderboard and Polish MT-Bench demonstrated the model’s robust capabilities in various NLP tasks and conversational abilities. In the Polish MT-Bench, it excelled particularly in Reasoning and Role-playing categories, showcasing its versatility and advanced understanding of context.
Quantization efforts aimed to make Bielik 7B v0.1 accessible on devices with limited computational resources, demonstrating a commitment to democratizing advanced language processing tools. These efforts ensure that the model’s benefits can be extended to a wider range of applications, potentially transforming technology interfaces for Polish speakers worldwide.
For more details on the development and capabilities of Bielik 7B v0.1, readers can refer to the full paper available at https://arxiv.org/pdf/2410.18565.