Text Classification
Transformers
Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
Instructions to use ElMad/trusting-pig-816 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ElMad/trusting-pig-816 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ElMad/trusting-pig-816")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ElMad/trusting-pig-816") model = AutoModelForSequenceClassification.from_pretrained("ElMad/trusting-pig-816", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f73d0d63187499ad41a8dbd0195b43c20667b2cc494c1bdf00a548ba0cc9db2
- Size of remote file:
- 598 MB
- SHA256:
- 18b400e38b5e3395b860d59595bdca6757b605523c7ba5f7960342cad1f4f577
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.