---
license: apache-2.0
language:
- en
- ko
- ja
- zh
---

# Tri-0.5B-Base


Tri-0.5B-Base is a \~500M parameter multilingual language model trained as an **early experimental run** before the Tri-7B training.

The model covers **English, Korean, Japanese, and Chinese**, with additional exposure to programming languages and mathematical reasoning.
Pretrained on \~1.26 trillion tokens, it serves as a lightweight base model for research, fine-tuning, and open-source community use - especially for advancing Korean LLM development.


## Model Summary

* Architecture: decoder-only Transformer (LLaMA-style)
* Parameters: \~472M (untied embeddings and LM head)
* Layers / hidden size / attention heads: 24 / 896 / 14
* Feedforward hidden size: 2,560 (SiLU-gated MLP)
* Context length: 4,096
* RoPE θ: 100,000
* Training precision: bfloat16
* Status: base pretraining only (no instruction tuning, no RLHF)


## Intended Use

* As a **foundation** for downstream fine-tuning and alignment.
* Research on multilingual pretraining and adaptation.


## Limitations

* Being a base model, outputs may be unsafe, incoherent, or factually incorrect.


## Usage

```python
from transformers import AutoTokenizer, AutoModelForCausalLM

name = "trillionlabs/Tri-0.5B-Base"
tok = AutoTokenizer.from_pretrained(name)
model = AutoModelForCausalLM.from_pretrained(
    name,
    torch_dtype="bfloat16",
    device_map="auto"
)

prompt = "Write a short paragraph about Hangul."
x = tok(prompt, return_tensors="pt").to(model.device)
y = model.generate(
    **x,
    max_new_tokens=128,
    do_sample=True,
    temperature=0.8,
    top_p=0.95
)
print(tok.decode(y[0], skip_special_tokens=True))
```

## License

This model is released under the **Apache 2.0 License**.
See [LICENSE](https://www.apache.org/licenses/LICENSE-2.0) for details.

---

## Citation

If you use this model, please cite it as:

```
@misc{trillionlabs_tri05b_base_2025,
  title  = {Tri-0.5B-Base},
  author = {Trillion Labs},
  year   = {2025},
  note   = {https://huggingface.co/trillionlabs/Tri-0.5B-Base}
}
```