Token Classification
Transformers
ONNX
Safetensors
modernbert
text-compression
context-compression
yscompress
Instructions to use decompute/yscompress-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use decompute/yscompress-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="decompute/yscompress-v1")# Load model directly from transformers import AutoTokenizer, YSCompressor tokenizer = AutoTokenizer.from_pretrained("decompute/yscompress-v1") model = YSCompressor.from_pretrained("decompute/yscompress-v1") - Notebooks
- Google Colab
- Kaggle
YSCompress v1
YSCompress v1 is an internal context/token compression model package.
Intended use
This package is intended for context compression and token-level keep/discard scoring in Decompute/Recompute inference systems.
Loading
from transformers import AutoConfig
cfg = AutoConfig.from_pretrained("decompute/yscompress-v1", token="hf_...")
print(cfg.model_type) # modernbert
Runtime note
model_type is intentionally retained as modernbert for Transformers compatibility. The deployment-facing architecture alias is YSCompressor.
Package contents
The package includes model weights, tokenizer assets, model configuration, optional ONNX assets if present, license, and third-party notices.
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