Instructions to use apkbala107/electratamilpos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apkbala107/electratamilpos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="apkbala107/electratamilpos")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("apkbala107/electratamilpos") model = AutoModelForTokenClassification.from_pretrained("apkbala107/electratamilpos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 714ce61b147361dc291e26845e62a7223aafd6768f6da9382a288f09b54adcb6
- Size of remote file:
- 38.8 MB
- SHA256:
- 0d32c903b9bc3e0ebc43b8665e5191280222e8a6f91d7f78c2dda5157054cf1f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.