Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/germanic_antielite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/germanic_antielite with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/germanic_antielite")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/germanic_antielite") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/germanic_antielite") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d1db03d4c351c511b6a83979c8f6974a833f2980d48c59e9e2d81672dae72b4
- Size of remote file:
- 5.3 kB
- SHA256:
- ed41dd538fdc315e8ee1a5e270727ec8abb0d2b98f94e3f25440add3976f5c81
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.