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README.md

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----
-language: mk
-tags:
-  - macedonian
-  - mistral
-  - llm
-  - nlp
-  - text-generation
-license: apache-2.0
-datasets:
-  - macedonian-wikipedia
-  - news-articles
-  - books
-metrics:
-  - perplexity
-  - bleu
-  - rouge
-  - accuracy
----
-
- # MK-LLM-Mistral: Fine-Tuned Macedonian Language Model  
-
-## 🌍 Overview  
-**MK-LLM-Mistral** is a **fine-tuned Macedonian language model**, built to enhance **text generation, comprehension, and NLP capabilities** in the Macedonian language.  
-This model is developed by **AI Now - Association for Artificial Intelligence in Macedonia** as part of the **MK-LLM initiative**, Macedonia's first open-source LLM project.
-
-📌 **Website:** [www.ainow.mk](https://www.ainow.mk)  
-📩 **Contact:** [contact@ainow.mk](mailto:contact@ainow.mk)  
-🛠 **GitHub Repository:** [MK-LLM](https://github.com/AI-now-mk/MK-LLM)  
-
----
-
-## 📌 Model Details  
-- **Architecture:** Fine-tuned **Mistral 7B**  
-- **Language:** Macedonian 🇲🇰  
-- **Training Data:** Macedonian Wikipedia, news articles, books, and open-source datasets  
-- **Tokenization:** Custom Macedonian tokenization  
-- **Framework:** [Hugging Face Transformers](https://huggingface.co/docs/transformers/index)  
-- **Model Type:** Causal Language Model (CLM)  
-
----
-
-## 🎯 Intended Use  
-This model is optimized for **Macedonian NLP tasks**, including:  
-✅ **Text Generation** – Macedonian text continuation and creative writing  
-✅ **Summarization** – Extracting key points from Macedonian documents  
-✅ **Question Answering** – Responding to Macedonian-language queries  
-✅ **Chatbots & Virtual Assistants** – Enhancing automated Macedonian-language interactions  
-
----
-
-## ⚠️ Limitations & Ethical Considerations  
-⚠️ This model **may not always be accurate** and could generate **biased or misleading** responses. It is recommended to:  
-- **Validate outputs** before using them in real-world applications.  
-- **Avoid using for critical decision-making** (e.g., legal, medical, financial).  
-- **Improve it further** with domain-specific fine-tuning.  
-
----
-
-## 🚀 How to Use the Model  
-You can load and run the model using **Hugging Face Transformers** in Python:
-
-### **🔹 Load the Model for Inference**
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-model_name = "ainowmk/MK-LLM-Mistral"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
-
-input_text = "Која е главната цел на вештачката интелигенција?"
-inputs = tokenizer(input_text, return_tensors="pt")
-output = model.generate(**inputs, max_length=50)
-
-print(tokenizer.decode(output[0], skip_special_tokens=True))
+# MK-LLM Model
+
+Macedonian Language Model based on Mistral architecture.
+
+## Usage
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("ainowmk/MK-LLM-Mistral")
+tokenizer = AutoTokenizer.from_pretrained("ainowmk/MK-LLM-Mistral")
+
+text = "Здраво, како си?"
+inputs = tokenizer(text, return_tensors="pt")
+outputs = model.generate(**inputs)
+print(tokenizer.decode(outputs[0]))
+```