Token Classification
Transformers
ONNX
Safetensors
English
kompress_v2
text-compression
modernbert
lora
kompress
Instructions to use ooognicki/weeizer-v2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ooognicki/weeizer-v2-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ooognicki/weeizer-v2-base")# Load model directly from transformers import HeadroomCompressorV2 model = HeadroomCompressorV2.from_pretrained("ooognicki/weeizer-v2-base", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e5dee6d93272976db64264a7fc80a7478865bb6f18869e1769e75b1063d8bbe
- Size of remote file:
- 3.94 MB
- SHA256:
- fd0b81ad56b3b9dc734397936ac066f2a73aea1722b42a074d9ebed47fc3da48
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