---
license: apache-2.0
language:
- en
library_name: transformers
tags:
- text-generation
- causal-lm
- transformer
- argonne
- pretrained
pipeline_tag: text-generation
---

# Argonne 2.0

A **4.9 billion parameter** decoder-only transformer language model trained from scratch.

## Model Architecture

| Component | Specification |
|-----------|--------------|
| **Parameters** | ~4.9B |
| **Layers** | 24 transformer blocks |
| **Hidden Size** | 4,080 |
| **Attention Heads** | 24 query / 8 key-value (GQA) |
| **Context Length** | 4,096 tokens |
| **Vocabulary Size** | 151,665 |

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model = AutoModelForCausalLM.from_pretrained(
    "PursuitOfDataScience/Argonne-2.0",
    torch_dtype=torch.bfloat16,
    device_map="auto",
    trust_remote_code=True
)
tokenizer = AutoTokenizer.from_pretrained("PursuitOfDataScience/Argonne-2.0", trust_remote_code=True)

prompt = "The future of AI is"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_length=256, do_sample=True, temperature=0.7)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

## License

Apache 2.0

## Citation

```bibtex
@misc{argonne2,
  author = {PursuitOfDataScience},
  title = {Argonne 2.0: A 4.9B Parameter Language Model},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/PursuitOfDataScience/Argonne-2.0}
}
```

## Links

- GitHub: [PursuitOfDataScience](https://github.com/PursuitOfDataScience)
- Hugging Face: [PursuitOfDataScience](https://huggingface.co/PursuitOfDataScience)