Create README.md

README.md

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+---
+license: apache-2.0
+language:
+- uk
+- en
+---
+
+# ukr-t5-small
+
+A compact T5-small model fine-tuned for Ukrainian language tasks, with base English understanding.
+
+## Model Description
+
+* **Base Model:** mT5-small 
+* **Fine-tuning Data:** Leipzig Corpora Collection (English & Ukrainian news from 2023)
+* **Tasks:**  
+    * Text summarization (Ukrainian)
+    * Text generation (Ukrainian)
+    * Other Ukrainian-centric NLP tasks
+
+## Technical Details
+* **Model Size:** 300 MB 
+* **Framework:** Transformers (Hugging Face)
+
+## Usage 
+
+**Installation**
+
+```bash
+pip install transformers
+```
+
+**Loading the Model**
+
+```python
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+tokenizer = AutoTokenizer.from_pretrained("path/to/ukr-t5-small")
+model = AutoModelForSeq2SeqLM.from_pretrained("path/to/ukr-t5-small")
+```
+
+**Example: Machine Translation**
+
+```python
+text = "(Text in Ukrainian here)"
+
+# Tokenize and translate
+inputs = tokenizer("summarize: " + text, return_tensors="pt", max_length=512, truncation=True)
+summary_ids = model.generate(inputs["input_ids"], num_beams=4, max_length=128)
+
+# Decode output 
+summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+print(summary)
+```
+
+## Limitations
+
+* The model's focus is on Ukrainian text processing, so performance on purely English tasks may be below that of general T5-small models.
+* Further fine-tuning may be required for optimal results on specific NLP tasks.
+
+## Dataset Credits
+
+This model was fine-tuned on the Leipzig Corpora Collection (specify if there's a particular subset within the collection that you used). For full licensing and usage information of the original dataset, please refer to [Leipzig Corpora Collection website](https://wortschatz.uni-leipzig.de/en/download)
+
+## Ethical Considerations
+
+* NLP models can reflect biases present in their training data. Be mindful of this when using this model for applications that have real-world impact.
+* It's important to test this model thoroughly across a variety of Ukrainian language samples to evaluate its reliability and fairness. 
+