Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use poooj/DistilBERTHateSpeechClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use poooj/DistilBERTHateSpeechClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="poooj/DistilBERTHateSpeechClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("poooj/DistilBERTHateSpeechClassification") model = AutoModelForSequenceClassification.from_pretrained("poooj/DistilBERTHateSpeechClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0fc5aa7ca807c9b1a0b27ad43ee611dc9e900369094db8f133261cefcfa971c
- Size of remote file:
- 268 MB
- SHA256:
- a205d9f89d1c9b1afa778ae392b5ebb612791eaf50b44ee8bb4d719685b442bc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.