OlmoEarth-v1-Nano (FP4 Quantized)

FP4 weight-quantized version of allenai/OlmoEarth-v1-Nano using nvidia-modelopt.

This is a quantized model, not a fine-tuned model.

Quantization Results

Metric Value
Quantization method nvidia-modelopt FP4 PTQ
Cosine similarity vs FP32 (mean) 0.978
Cosine similarity vs FP32 (min) 0.977
Quantizer nodes 111 (25 Linear + 12 Conv2d)
Save/load roundtrip 1.000 (perfect)
Model size 5.3 MB
GPU tested RTX 5090 (Blackwell)

Usage

import torch, copy
import modelopt.torch.opt as mto
from huggingface_hub import hf_hub_download
from olmoearth_pretrain.model_loader import ModelID, load_model_from_id

model = load_model_from_id(ModelID.OLMOEARTH_V1_NANO, load_weights=True).cuda().eval()
encoder = copy.deepcopy(model.encoder)

ckpt = hf_hub_download("2imi9/olmoearth-nano-fp4", "model.pth")
mto.restore(encoder, ckpt)
encoder.cuda().eval()

output = encoder(sample, patch_size=2)
embedding = output["project_aggregated"]  # [B, 128]

Hardware

  • FP4: Blackwell (RTX 5090, B100)
  • CUDA 13.0+
  • nvidia-modelopt >= 0.31
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