Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+datasets:
+- wikimedia/wikipedia
+- roneneldan/TinyStories
+- ajibawa-2023/Children-Stories-Collection
+- stas/c4-en-10k
+pipeline_tag: text-generation
+---
+
+# Serayuki-2B
+
+**Model Developer**: Shoukaku07
+<br>
+**Model Type**: Causal Language Model
+
+## Example Usage
+
+Using Hugging Face Transformers:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("SeraphyneLab/Serayuki-2B")
+tokenizer = AutoTokenizer.from_pretrained("SeraphyneLab/Serayuki-2B")
+
+input_text = "Once upon a time"
+inputs = tokenizer(input_text, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=128)
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## License
+
+This model is licensed under the [MIT License](https://opensource.org/licenses/MIT).
+
+## Tokenizer Notice
+
+This model was trained from scratch; however, it uses the tokenizer from Meta’s LLaMA 3.2 3B Instruct model. As such, the tokenizer is subject to Meta’s [LLaMA 3 license](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct/blob/main/LICENSE.txt). Please review their terms before using this model or tokenizer in commercial applications.