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Blood Cancer Resnet18

Fine-tuned ResNet18 for classifying blood cell images into 4 classes.

Sourcehuggingface.co/NaumanHa/blood-cancer-resnet18/tree/4bf66391a033514897ed890613e711525752db0d
KindOtherVersionRevision 4bf6639Cgrade

Model source

Kind
Other
File size
42.6–42.7 MB
Version
vRevision 4bf6639
Updated
Oct 24, 2026
Downloads
4
Source
Hugging Face

Source description

Blood Cell Cancer Classifier (ResNet18)

Fine-tuned ResNet18 for classifying blood cell images into 4 classes.

Classes

  1. Benign
  2. Malignant Pre-B
  3. Malignant Pro-B
  4. Malignant early Pre-B

Performance

  • Validation Accuracy: 99.38%

Usage

from huggingface_hub import PyTorchModelHubMixin
import torch.nn as nn
from torchvision import models

class BloodCancerResNet18(nn.Module, PyTorchModelHubMixin):
    def __init__(self, num_classes=4):
        super().__init__()
        base = models.resnet18(weights=None)
        base.fc = nn.Linear(base.fc.in_features, num_classes)
        self.model = base

    def forward(self, x):
        return self.model(x)

model = BloodCancerResNet18.from_pretrained("your-username/blood-cancer-resnet18")
model.eval()

Training Data

Trained on the Blood Cell Cancer ALL-4class dataset.

Sources

1 source
Hugging FacePrimaryVersion 4bf66391a033514897ed890613e711525752db0d
huggingface.co/NaumanHa/blood-cancer-resnet18/tree/4bf66391a033514897ed890613e711525752db0d

Verified Aug 19

Model artifacts

2 artifacts

blood_cancer_resnet18.onnx

onnx · 42.6 MB · SHA-256 6807ec40bd2d…0943 · Hugging Face

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model.safetensors

safetensors · 42.7 MB · SHA-256 e595bc52fe8f…e833 · Hugging Face

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Source excerpts

2 excerpts
ReadmeAug 19huggingface.co/NaumanHa/blood-cancer-resnet18

--- license: mit tags: - image-classification - pytorch - medical-imaging - resnet18 --- # Blood Cell Cancer Classifier (ResNet18) Fine-tuned ResNet18 for classifying blood cell images into 4 classes. ## Classes 0. Benign 1. Malignant Pre-B 2. Malignant Pro-B 3. Malignant early Pre-B ## Performance - Validation Accuracy: 99.38% ## Usage ```python from huggingface_hub import PyTorchModelHubMixin import torch.nn as nn from torchvision import models class BloodCancerResNet18(nn.Module, PyTorchModelHubMixin): def __init__(self, num_classes=4): super().__init__() base = models.resnet18(weights=None) base.fc = nn.Linear(base.fc.in_features, num_classes) self.model = base def forward(self, x): return self.model(x) model = BloodCancerResNet18.from_pretrained("your-username/blood-cancer-resnet18") model.eval() ``` ## Training Data Trained on the [Blood Cell Cancer ALL-4class dataset](https://www.kaggle.com/datasets/mohammadamireshraghi/blood-cell-cancer-all-4class).

NoteAug 19huggingface.co/NaumanHa/blood-cancer-resnet18

Source context: 4 downloads · 0 likes · Pipeline image-classification · Repo NaumanHa/blood-cancer-resnet18