Text Classification
Transformers
PyTorch
TensorBoard
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use SiddharthaM/mdeberta-profane-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SiddharthaM/mdeberta-profane-final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SiddharthaM/mdeberta-profane-final")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SiddharthaM/mdeberta-profane-final") model = AutoModelForSequenceClassification.from_pretrained("SiddharthaM/mdeberta-profane-final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from SiddharthaM/mdeberta-profane-final: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/SiddharthaM/mdeberta-profane-final/resolve/main/tokenizer.json
- Command line
-
hf download hf://SiddharthaM/mdeberta-profane-final/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/SiddharthaM/mdeberta-profane-final/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- 5531c89940052da7414e157b43208431ec2f0d93811cc0a82c6e3d06e543ec30
- Size of remote file:
- 16.3 MB
- SHA256:
- 5b128f3eb3c16ebe674b34492da141a26ed841f594763465ade051b15d71650c
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