Atlantis-Pyramid 14B (Glyph)
Atlantis-Pyramid 14B (Glyph) is the flagship model of the Coralfil OS Atlantis project.
It is a fine-tuned version of Qwen/Qwen2.5-14B-Instruct (~14.7B parameters, verified 2026-08-10: 48 layers, hidden 5120),
specialized for marine restoration science, aquaculture chemistry,
dynamic oceanography modeling, and coral reef ecosystem analysis.
Model Details
| Property | Value |
|---|---|
| Base Model | Qwen/Qwen2.5-14B-Instruct |
| Parameters | ~14.7B (renamed from '32B' — measured weight dims are 14B-class) |
| Fine-Tuning Method | LoRA SFT (r=16, alpha=32) |
| Target Modules | q_proj, v_proj, k_proj, o_proj, gate_proj, up_proj, down_proj |
| Precision | bfloat16 / 4-bit NF4 |
| Training Data | Coralfil validated marine science corpus |
| Build Date | 2026-07-12 |
Training
The model was fine-tuned using Supervised Fine-Tuning (SFT) with the trl
library's SFTTrainer. LoRA adapters were trained in 4-bit precision
for memory efficiency and then merged into the base model for inference.
Hyperparameters:
- Learning rate: 2e-4 (cosine schedule with 10% warmup)
- Batch size: 2 per device, gradient accumulation 4
- Weight decay: 0.01
- Max sequence length: 2048
Usage
With Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
model = AutoModelForCausalLM.from_pretrained(
"Coralfil/Atlantis-Pyramid-32B",
torch_dtype=torch.bfloat16,
device_map="auto",
)
tokenizer = AutoTokenizer.from_pretrained("Coralfil/Atlantis-Pyramid-32B")
prompt = "Describe the optimal conditions for staghorn coral restoration."
messages = [
{"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer([text], return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.7)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
With vLLM
vllm serve Coralfil/Atlantis-Pyramid-32B --dtype bfloat16 --max-model-len 4096
Intended Use
This model is designed for research and operational use within the Coralfil OS ecosystem. It excels at:
- Marine biology question answering
- Coral reef ecosystem analysis
- Aquaculture parameter optimization
- Oceanographic data interpretation
- Environmental compliance assessment
Limitations
- This model is specialized for marine science domains and may underperform on unrelated tasks compared to the general-purpose base model.
- Outputs should be validated by domain experts for critical decisions.
- Not intended for medical or safety-critical applications.
License
Apache 2.0 -- see LICENSE for details.
Citation
@misc{atlantis-pyramid-2026,
title={Atlantis-Pyramid-32B: A Fine-Tuned 32B Model for Marine Science},
author={Coralfil Team},
year={2026},
publisher={Hugging Face},
url={https://huggingface.co/Coralfil/Atlantis-Pyramid-32B}
}