Text Classification
PEFT
Safetensors
Transformers
Hebrew
dpo
lora
trl
hebrew
offensive-language-detection
content-moderation
explainable-ai
reasoning
Instructions to use KevynKrancenblum/hebrew-offensive-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use KevynKrancenblum/hebrew-offensive-detection with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("dicta-il/dictalm2.0-instruct") model = PeftModel.from_pretrained(base_model, "KevynKrancenblum/hebrew-offensive-detection") - Transformers
How to use KevynKrancenblum/hebrew-offensive-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KevynKrancenblum/hebrew-offensive-detection")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("KevynKrancenblum/hebrew-offensive-detection", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ef7f0a2d0a664cd1f6a878573d2ae897890465e2b7ef0baf17a096169a0d634
- Size of remote file:
- 6.33 kB
- SHA256:
- c59aaa6f6ca5c93f2685a0a97ec31aaacbdf3b8618e2b77cd9f9f838421495f9
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