Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Denyol/FakeNews-bert-large-cased-grad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Denyol/FakeNews-bert-large-cased-grad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Denyol/FakeNews-bert-large-cased-grad")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Denyol/FakeNews-bert-large-cased-grad") model = AutoModelForSequenceClassification.from_pretrained("Denyol/FakeNews-bert-large-cased-grad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 065d337ffc7e90c9d2a13f66477d53768177f6bf05a0dfee95f8ae3bf8b994a6
- Size of remote file:
- 1.33 GB
- SHA256:
- f0720e458fcf35fb3eb917fd73ba51a64a251dfcf5257e8c4606679734c71e2c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.