Text Classification
Transformers
TensorBoard
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use Af2024ma/distilbert-small-offensive-classification-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Af2024ma/distilbert-small-offensive-classification-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Af2024ma/distilbert-small-offensive-classification-test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Af2024ma/distilbert-small-offensive-classification-test") model = AutoModelForSequenceClassification.from_pretrained("Af2024ma/distilbert-small-offensive-classification-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Af2024ma/distilbert-small-offensive-classification-test: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/Af2024ma/distilbert-small-offensive-classification-test/resolve/main/tokenizer.json
- Command line
-
hf download hf://Af2024ma/distilbert-small-offensive-classification-test/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Af2024ma/distilbert-small-offensive-classification-test/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- 7972b74f751543b10a92008c21570659bc5107a6660ef3b5f10c811e6c363237
- Size of remote file:
- 16.3 MB
- SHA256:
- da06fa6bca6c8ccbd98d524d3baaa25a9e0f8690d9d31e52f72e1fed685ae465
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.