---
license: mit
datasets:
- wikimedia/wikipedia
- roneneldan/TinyStories
- ajibawa-2023/Children-Stories-Collection
- stas/c4-en-10k
pipeline_tag: text-generation
---

# Serayuki-1B

**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-1B")
tokenizer = AutoTokenizer.from_pretrained("SeraphyneLab/Serayuki-1B")

input_text = "Once upon a time"
inputs = tokenizer(input_text, return_tensors="pt").to("cuda")
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.