Instructions to use Apoksk1/convbert-offensive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Apoksk1/convbert-offensive with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Apoksk1/convbert-offensive")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Apoksk1/convbert-offensive") model = AutoModelForSequenceClassification.from_pretrained("Apoksk1/convbert-offensive", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Apoksk1/convbert-offensive: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/Apoksk1/convbert-offensive/resolve/main/training_args.bin
- Command line
-
hf download hf://Apoksk1/convbert-offensive/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Apoksk1/convbert-offensive/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- 9d6ebe4fc14194ede37cecb83e470f9d8b46f00e9a3fdc8f2029786d53798062
- Size of remote file:
- 4.98 kB
- SHA256:
- bad73a2904331688e4272bbd190f9ef9226ce0257169cd7901abb713664e9aaa
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