Update README.md

README.md

@@ -1,5 +1,7 @@
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 license: apache-2.0
+language:
+- pl
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 <p align="center">
   <img src="https://pllum.org.pl/_nuxt/PLLuM_logo_RGB_color.DXNEc-VR.png">
@@ -50,7 +52,7 @@ Below is a summary of the main PLLuM models, including their licenses, bases, an
 
 ### Model Development
 - **Pretraining**: All models were pretrained or continued-pretrained on large-scale Polish corpora (up to 150B tokens) plus a range of additional Slavic/Baltic and English texts.
-- **Instruction Fine-Tuning**: We refined the models on manually curated Polish “organic instructions,” converted instructions from premium Polish corpora, and synthetic instructions generated by strong LLMs.
+- **Instruction Fine-Tuning**: We refined the models on manually curated Polish “organic instructions” (approx. 40k), converted instructions from premium Polish corpora (approx. 50k), and synthetic instructions generated by strong LLMs (approx. 10k).
 - **Alignment and Preference Learning**: Manually annotated preference data taught the models to produce safer, balanced, and contextually appropriate responses, even in adversarial or sensitive cases.
 - **Domain-Specific Adaptations**: Specialized RAG-based (Retrieval Augmented Generation) models were developed for tasks like public administration, demonstrating strong performance in complex information retrieval and question answering.
 
@@ -229,4 +231,4 @@ We welcome feedback, collaboration, and further exploration of PLLuM models!
 Project financed by the Minister of Digital Affairs under the targeted subsidy No. 1/WI/DBiI/2023: *“Responsible development of the open large language model PLLuM (Polish Large Language Model) to support breakthrough technologies in the public and economic sector, including an open, Polish-language intelligent assistant for petitioners.”*
 
 **Funding Amount:** 14,504,392.00 PLN  
-**Contract Signing Date:** 2024-01-22
+**Contract Signing Date:** 2024-01-22