Text Classification
Transformers
PyTorch
toxic_comment_xlmr
feature-extraction
toxicity
content-moderation
multilingual
multi-label
xlm-roberta
custom_code
Eval Results (legacy)
Instructions to use Deeptanshuu/mill-screen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Deeptanshuu/mill-screen with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Deeptanshuu/mill-screen", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Deeptanshuu/mill-screen", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Deeptanshuu/mill-screen: direct link, hf CLI and curl.
- Browser
- Download file 2.26 GB
-
https://huggingface.co/Deeptanshuu/mill-screen/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Deeptanshuu/mill-screen/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Deeptanshuu/mill-screen/resolve/main/pytorch_model.bin
2.26 GB
- Xet hash:
- 2a677323130a9b63f3b3d6028b68d149c6fddfc904489c440d8f823f6deb24aa
- Size of remote file:
- 2.26 GB
- SHA256:
- 54b4fd10ad5e369324fe9764061cff6fc5d0d97218c5929407c3cfcbd366bb0e
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