Feature Extraction
Transformers
Safetensors
English
Chinese
qwen3_dflash2
draftfit
speculative-decoding
dflash2
humanizer
text-rewriting
rewriting
paraphrase
style-transfer
gemma4
custom_code
Instructions to use jayyun98/Humanizer-12B-Draftfit-DFlash2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jayyun98/Humanizer-12B-Draftfit-DFlash2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jayyun98/Humanizer-12B-Draftfit-DFlash2", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jayyun98/Humanizer-12B-Draftfit-DFlash2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
11 days ago
-
Publish Humanizer family draft and verified MLX comparison
Verified signature7931fb2