Instructions to use Unggi/hate_speech_classifier_KcElectra with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Unggi/hate_speech_classifier_KcElectra with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Unggi/hate_speech_classifier_KcElectra")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Unggi/hate_speech_classifier_KcElectra") model = AutoModelForSequenceClassification.from_pretrained("Unggi/hate_speech_classifier_KcElectra", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
This is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.5a752bf
-
Create score_record.txt
ca18c1b
-
Upload pytorch_model.bin
ab91a0b -
Delete pytorch_model.bin
ed6a9af
-
Upload 6 files
4bc46c3 -
Delete vocab.txt
c5901c0 -
Delete tokenizer_config.json
7b20a5f -
Delete tokenizer.json
895bf9f -
Delete special_tokens_map.json
75df79b -
Delete pytorch_model.bin
655345d -
Delete config.json
8d8dc44 -
Upload 6 files
ceb7f4c
-
initial commit
08015ce