Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use SiddharthaM/mbert-profane-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SiddharthaM/mbert-profane-final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SiddharthaM/mbert-profane-final")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SiddharthaM/mbert-profane-final") model = AutoModelForSequenceClassification.from_pretrained("SiddharthaM/mbert-profane-final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SiddharthaM/mbert-profane-final: direct link, hf CLI and curl.
- Browser
- Download file 711 MB
-
https://huggingface.co/SiddharthaM/mbert-profane-final/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SiddharthaM/mbert-profane-final/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SiddharthaM/mbert-profane-final/resolve/main/pytorch_model.bin
711 MB
- Xet hash:
- 795640e4bf5cda857ef52fe6ff5a0210fbeb859168d01fb71df4cf0d31f649f5
- Size of remote file:
- 711 MB
- SHA256:
- dec7c6b3ad1bf95b31f6274fa052d5e17a22289082ce10b4db80a2003ef907e7
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