Instructions to use Prem11100/layoutlmv3-Sample1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prem11100/layoutlmv3-Sample1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Prem11100/layoutlmv3-Sample1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("Prem11100/layoutlmv3-Sample1") model = AutoModelForSequenceClassification.from_pretrained("Prem11100/layoutlmv3-Sample1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
092a988 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:90e54f290de8776cf9d74a7cd1e69f1292db5b02fa33c40f4ffd516ffc8536cd
size 503764657
|