Argonne-2.0

PursuitOfDataScience/Argonne-2.0

Argonne-2.0 is a text generation model from PursuitOfDataScience. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.

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

Downloads · 30 days

43% of all-time downloads

All-time downloads

129

Public

Parameters

5.5B

22.1 GB on disk

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Public

Hugging Face

Repo makeup

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.safetensors22.1 GB · 100%

At a glance

Task: Text Generation
Library: transformers
License: apache-2.0
Model type: argonne2
Access: Public
Created: Jan 24, 2026
Updated: Jan 24, 2026
SHA: 95e5b13a

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Model card

From the Hugging Face model README

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

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

@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}
}