Added code example

README.md

@@ -48,6 +48,26 @@ The model was trained for 1.5 epochs over 12 days on the [LUMI supercomputer](ht
 
 This model serves as a multilingual base LLM, suitable for instruction tuning, research, and language understanding tasks in low- and high-resource European languages.
 
+
+### Use with transformers
+
+Quick start with `Transformers` both for GPU and CPU enabled envs:
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+import torch
+
+model_name = "minilingua-ai/MiniLingua-1b"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto", dtype=torch.float16)
+gen = pipeline("text-generation", model=model, tokenizer=tokenizer, trust_remote_code=True)
+
+prompt = "Translate from Bulgarian: Здравейте! Как сте? Translation:"
+out = gen(prompt, max_new_tokens=128, do_sample=False)
+print(out[0])
+```
+
 ### License
 
 Apache 2.0 — free for research and commercial use, subject to the terms.