Update README.md

README.md

@@ -1,7 +1,62 @@
 ---
+library_name: transformers
 license: apache-2.0
 ---
 
-## Model Card for MisterUkrainian DPO ##
+# Model card for Mistral-Instruct-Ukrainian-SFT
 
-This is a DPO iteration of...
+Supervised finetuning of Mistral-7B-Instruct-v0.2 on Ukrainian datasets.
+
+
+## Instruction format
+
+In order to leverage instruction fine-tuning, your prompt should be surrounded by `[INST]` and `[/INST]` tokens.
+
+E.g.
+```
+text = "[INST]Відповідайте лише буквою правильної відповіді: Елементи експресіонізму наявні у творі: A. «Камінний хрест», B. «Інститутка», C. «Маруся», D. «Людина»[/INST]"
+```
+
+This format is available as a [chat template](https://huggingface.co/docs/transformers/main/chat_templating) via the `apply_chat_template()` method:
+
+## Model Architecture
+This instruction model is based on Mistral-7B-v0.2, a transformer model with the following architecture choices:
+- Grouped-Query Attention
+- Sliding-Window Attention
+- Byte-fallback BPE tokenizer
+
+## Datasets
+- [UA-SQUAD](https://huggingface.co/datasets/FIdo-AI/ua-squad/resolve/main/ua_squad_dataset.json)
+- [Ukrainian StackExchange](https://huggingface.co/datasets/zeusfsx/ukrainian-stackexchange)
+- [UAlpaca Dataset](https://github.com/robinhad/kruk/blob/main/data/cc-by-nc/alpaca_data_translated.json)
+- [Ukrainian Subset from Belebele Dataset](https://github.com/facebookresearch/belebele)
+- [Ukrainian Subset from XQA](https://github.com/thunlp/XQA)
+  
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "Radu1999/Mistral-Instruct-Ukrainian-SFT"
+messages = [{"role": "user", "content": "What is a large language model?"}]
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+
+outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print(outputs[0]["generated_text"])
+```
+
+## Author
+
+Radu Chivereanu