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 pytorch_model.bin from dafqi/DistilBERT-Hoax-Detection: direct link, hf CLI and curl.
- Browser
- Download file 272 MB
-
https://huggingface.co/dafqi/DistilBERT-Hoax-Detection/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dafqi/DistilBERT-Hoax-Detection/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dafqi/DistilBERT-Hoax-Detection/resolve/main/pytorch_model.bin
272 MB
- Xet hash:
- 5172d5fe4fc9ed6fd840f9bf6bfeeaa4c27c422676e04c458653059bdce966e7
- Size of remote file:
- 272 MB
- SHA256:
- bb7aaebc02e6fd58daa1a99a6f3a881dcb79b925138049819eb8810b09f3fa15
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