Add README

README.md

@@ -1,25 +1,62 @@
 ---
+configs:
+- config_name: default
+  data_files:
+  - path: data/train-*
+    split: train
 dataset_info:
+  dataset_size: 619476
+  download_size: 244184
   features:
-  - name: keyword
-    dtype: string
-  - name: topic
-    dtype: string
-  - name: language
-    dtype: string
+  - dtype: string
+    name: keyword
+  - dtype: string
+    name: topic
+  - dtype: string
+    name: language
   - name: generated_text
     struct:
-    - name: text
-      dtype: string
+    - dtype: string
+      name: text
   splits:
   - name: train
     num_bytes: 619476
     num_examples: 451
-  download_size: 244184
-  dataset_size: 619476
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+language:
+- mk
+license:
+- apache-2.0
+size_category:
+- <1K
+tags:
+- legal
+- synthetic
+- text
+- synthgenai
+task_categories:
+- text-generation
 ---
+
+
+
+## Description
+
+- Topic: Professional Documents
+- Domains: 
+  - Legal Documents
+  - Technical Manuals
+  - Business Reports
+  - Education Materials
+  - Scientific Research
+- Focus: This dataset contains professional documents in Macedonian.
+- Number of Entries: 451
+- Dataset Type: Raw Dataset
+- Model Used: bedrock/us.anthropic.claude-3-5-sonnet-20240620-v1:0
+- Language: Macedonian
+- Additional Information:
+  - The dataset covers a wide range of professional fields, providing a diverse collection of document types.
+  - It serves as a valuable resource for natural language processing tasks in the Macedonian language, particularly for professional and technical contexts.
+  - The synthetic nature of the dataset ensures privacy compliance while maintaining the characteristics of authentic professional documents.
+- Generated by: SynthGenAI Package
+
+This synthetic dataset comprises 451 entries of professional documents in the Macedonian language. It spans across multiple domains, including legal, technical, business, educational, and scientific fields. The raw dataset format makes it suitable for various text generation and analysis tasks specific to professional Macedonian content. Researchers and developers working on Macedonian language models, especially those focused on professional and technical writing, may find this dataset particularly useful.