metadata
language:
- en
license: mit
tags:
- llama
- pran
- frozen-fork
- base-model
- text-generation
pipeline_tag: text-generation
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.