Instructions to use Saving-Willy/template_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Saving-Willy/template_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Saving-Willy/template_classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Saving-Willy/template_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 496 Bytes
fe3b346 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | from typing import Dict, List, Optional, Tuple
import timm
import torch
from pytorch_lightning import LightningModule
class TemplateClassifier(LightningModule):
def __init__(self, config: dict):
super().__init__()
# NN architecture
self.backbone = timm.create_model(
#SPECIFY HERE YOUR MODEL
)
def forward(self, x: torch.Tensor) -> torch.Tensor:
# WRITE YOU CODE HERE
predictions=None
return predictions
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