Pran

Pran is a frozen sibling copy of teddyoas/Agron, created from Agron commit a311e94 (2026-10-22).

Pran is intentionally left alone: it is not trained, fine-tuned, or modified in this iteration. Its weights are bit-for-bit the published Agron weights at that commit, and it exists so a second, independent pretraining run can start from the same base without touching Agron.

Model details

Property	Value
Architecture	LlamaForCausalLM
Parameters	~50.3M
Hidden size	512
Layers	8
Attention heads	4 (4 KV heads)
Intermediate size	2048
Context length	512
Vocab size	16384
Precision	fp32
Tokenizer	PreTrainedTokenizerFast (same as Agron)

The config, tokenizer and model.safetensors are exact copies of Agron at the commit above.

Status

• Training: none. Pran has no additional training steps applied.
• Agron, by contrast, is being continued-pretrained on programming languages and cybersecurity in the same iteration.
• Pran is reserved for a separate, later pretraining objective.

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

tok = AutoTokenizer.from_pretrained("teddyoas/Pran")
model = AutoModelForCausalLM.from_pretrained("teddyoas/Pran")

Pran is a small experimental base model. It is not instruction tuned and will produce raw, often incoherent continuations.

License

MIT, inherited from Agron.