Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

Stemson-AI
/
cmmp-resnet18-256

Image Feature Extraction
PyTorch
microscopy
electron-microscopy
HAADF-STEM
contrastive-learning
CLIP
materials-science
image-retrieval
metadata-embedding
resnet
Model card Files Files and versions
xet
Community
cmmp-resnet18-256
45.5 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
cgeorgiaw's picture
cgeorgiaw HF Staff
Update: retrained on the new 7,330-image CMMP dataset (ResNet-18, crop 256, meta 256x3, batch 512). Top-1 0.844, mean linear-probe R^2 0.691.
4525296 verified 25 days ago
  • .gitattributes
    1.52 kB
    initial commit about 1 month ago
  • README.md
    4.96 kB
    Update: retrained on the new 7,330-image CMMP dataset (ResNet-18, crop 256, meta 256x3, batch 512). Top-1 0.844, mean linear-probe R^2 0.691. 25 days ago
  • config.json
    518 Bytes
    Update: retrained on the new 7,330-image CMMP dataset (ResNet-18, crop 256, meta 256x3, batch 512). Top-1 0.844, mean linear-probe R^2 0.691. 25 days ago
  • linear_probe_metadata.json
    1.74 kB
    Update: retrained on the new 7,330-image CMMP dataset (ResNet-18, crop 256, meta 256x3, batch 512). Top-1 0.844, mean linear-probe R^2 0.691. 25 days ago
  • model.pth

    Detected Pickle imports (5)

    • "torch._utils._rebuild_tensor_v2",
    • "collections.OrderedDict",
    • "torch.LongStorage",
    • "torch.FloatStorage",
    • "torch.DoubleStorage"

    What is a pickle import?

    45.4 MB
    xet
    Update: retrained on the new 7,330-image CMMP dataset (ResNet-18, crop 256, meta 256x3, batch 512). Top-1 0.844, mean linear-probe R^2 0.691. 25 days ago
  • training_log.csv
    63 kB
    Update: retrained on the new 7,330-image CMMP dataset (ResNet-18, crop 256, meta 256x3, batch 512). Top-1 0.844, mean linear-probe R^2 0.691. 25 days ago