Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use dafqi/DistilBERT-Hoax-Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dafqi/DistilBERT-Hoax-Detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dafqi/DistilBERT-Hoax-Detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dafqi/DistilBERT-Hoax-Detection") model = AutoModelForSequenceClassification.from_pretrained("dafqi/DistilBERT-Hoax-Detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dafqi/DistilBERT-Hoax-Detection: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/dafqi/DistilBERT-Hoax-Detection/resolve/main/training_args.bin
- Command line
-
hf download hf://dafqi/DistilBERT-Hoax-Detection/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dafqi/DistilBERT-Hoax-Detection/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 29926f78b8d88a634c78941c108e7b7e8ad085f595c5827fa891a4a0d9e80107
- Size of remote file:
- 3.96 kB
- SHA256:
- 7b73958194c4aef68a53e9239d98a7a97b91687fab0ab72cfa94c2d557f15db8
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