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View details ↗qwen3-4b-finqa-v2
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View details ↗p3-lenpen-qwen3-1.7b-lam0.6
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View details ↗TigerCoder-12B
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View details ↗yolos-tiny-signature-detection
mdefranceYOLOS model finetuned to detect handwritten signatures in document images using [tech4humans/signature-detection](https://huggingface.co/datasets/tech4humans/signature-detection) dataset. Original YOLOS was introduced in the paper You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detection by Fang et al. and first released in this repository. YOLOS is a Vision Transformer (ViT) trained using the DETR loss. Despite its simplicity, a base-sized YOLOS model is able to achieve 42 AP on COCO validation 2017 (similar to DETR and more complex frameworks such as Faster R-CNN).
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View details ↗gemma-4-e-GGUF
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View details ↗Indonesian BERT Base Sentiment Classifier is a sentiment-text-classification model. The model was originally the pre-trained IndoBERT Base Model (phase1 - uncased) model using Prosa sentiment dataset
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View details ↗ACEStep-XL-Regrind-V1
mdmachine**Fine-tuned VAE decoder and DiT LoRA targeting the Oobleck hum artifact series at the weight level** ACEStep XL Turbo and the Oobleck VAE produce a characteristic harmonic artifact present in all generations. The artifact has two independent origins: **VAE decoder bias** — static reconstruction bias baked into the Oobleck decoder during its original training. Present at consistent amplitude across all generations, independent of length. Characterized via Ableton EQ Eight direct measurement:
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View details ↗deberta-ai-detector-v3
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View details ↗Qwen3.5-35B-A3B-heretic-v3-GGUF
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