Instructions to use nanelimon/zeltech-akbank-hackathon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nanelimon/zeltech-akbank-hackathon with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nanelimon/zeltech-akbank-hackathon")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nanelimon/zeltech-akbank-hackathon") model = AutoModelForSequenceClassification.from_pretrained("nanelimon/zeltech-akbank-hackathon", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 55bdf804366dc9eac0cea6218f3658990bfaa2fc7b828f81be4cbe84d17aab17
- Size of remote file:
- 443 MB
- SHA256:
- 0872729bfca6ad69083cb04ea413b97bbb0579858750532b826884eebf9a814e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.