Text Classification
Transformers
PyTorch
TensorBoard
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use SiddharthaM/mdeberta-hate-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SiddharthaM/mdeberta-hate-final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SiddharthaM/mdeberta-hate-final")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SiddharthaM/mdeberta-hate-final") model = AutoModelForSequenceClassification.from_pretrained("SiddharthaM/mdeberta-hate-final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SiddharthaM/mdeberta-hate-final: direct link, hf CLI and curl.
- Browser
- Download file 1.12 GB
-
https://huggingface.co/SiddharthaM/mdeberta-hate-final/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SiddharthaM/mdeberta-hate-final/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SiddharthaM/mdeberta-hate-final/resolve/main/pytorch_model.bin
1.12 GB
- Xet hash:
- 79988e4ae36e947a5e1f7133d17a1df216b1bb9ff12b81cd1499ebf3bd860139
- Size of remote file:
- 1.12 GB
- SHA256:
- 0e190633aabf485f33a351ac7e8dba37188fd3cfcb7a011972f70f18c87af33b
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