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ModelHugging Face

Granite Geospatial Biomass

This model is based on the paper TerraTorch: The Geospatial Foundation Models Toolkit.

Other
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ModelHugging Face

Voila Autonomous Preview

Voila: Voi ce- La nguage Foundation Models

Othermaitrix-org/Voila-base
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ModelHugging Face

Segment Anything 2 Onnx Models

ONNX exports of Meta's SAM 2 image-segmentation backbones, packaged for direct use with onnxruntime and AnyLabeling.

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ModelHugging Face

EBEN Rigid In Ear Microphone

Developed by: Cnam-LMSSC Model: EBEN(M=4,P=2,Q=4) (see publication in IEEE TASLP - arXiv link) Language: French License: MIT Training dataset: speechclean subset of Cnam-LMSSC/vibravox (see VibraVox paper on arXiV)...

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ModelHugging Face

Whisper Base Cv11

A plain openai/whisper-base (unmodified architecture) fine-tuned on the 11 languages of the CC0 Whispered corpus. This is the matched scientific control for burakaydinofficial/whisper-base-mla-cv11 — trained...

Text modelopenai/whisper-base
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ModelHugging Face

Llava Llama 3 8b Pretrain

llava-llama-3-8b-pretrain is a LLaVA projector pretrained from Meta-Llama-3-8B-Instruct and CLIP-ViT-Large-patch14-336 on LLaVA-Pretrain dataset by XTuner.

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ModelHugging Face

Huihui Gemma 4 E2B It Qat Q4 0 Unquantized Abliterated

This is an uncensored version of google/gemma-4-E2B-it-qat-q40-unquantized created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to...

Text modelgoogle/gemma-4-E2B-it-qat-q4_0-unquantized
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ModelHugging Face

Matcha Clips 224 Fintuned 5

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set: Loss: 1.5168 Accuracy: 0.7326

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ModelHugging Face

Images 3Dmodel

This project showcases an experimental pipeline that bridges natural language prompts to 3D model generation using a modified version of a pre-trained multi-view diffusion model.

UNet
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ModelHugging Face

v63 Public Guard LoRA R64 Lr8e5 Ep2

This model is a fine-tuned version of OpenOneRec/OneReason-0.8B-pretrain-competition on the expv63publicuservideoliveguard dataset.

OtherOpenOneRec/OneReason-0.8B-pretrain-competition
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ModelHugging Face

Sandglasset 2spk Polyvox

This repository contains the fine-tuned 2-speaker Sandglasset speech separation checkpoint used in the PolyVOX Samsung EnnovateX hackathon pipeline for real-time multi-user smart assistant command understanding in...

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ModelHugging Face

Siglip2 So400m Patch16 512 Guj 32768

This model is a 22.63% smaller version of google/siglip2-so400m-patch16-512 optimized for Gujarati language via vocabulary size reduction using the trimming method. This trimmed model should perform similarly to the...

Text modelgoogle/siglip2-so400m-patch16-512
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ModelHugging Face

Qwen3 Asr 1.7b Mizonal3 E2 Lus v2026.06

> Disclaimer / Notice: Details for these are in Peer Review and publications of the paper will be made available soon for more details.

Text modelQwen/Qwen3-ASR-1.7B
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ModelHugging Face

Siglip2 Large Patch16 512 Bak 32768

This model is a 25.91% smaller version of google/siglip2-large-patch16-512 optimized for Bashkir language via vocabulary size reduction using the trimming method. This trimmed model should perform similarly to the...

Text modelgoogle/siglip2-large-patch16-512
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ModelHugging Face

Ddpm Celebahq Finetuned Butterflies 4epochs Ng

Used a small butterfly dataset to finetune the ddpm-celebahq-256, originally trained on celebrity photos: As expected, the resulets are not great did not move further to finetune yet

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ModelHugging Face

REAL TSE BSRNN CoreML

Native Core ML conversion of the REAL-TSE Challenge spkemb100 baseline. It extracts an enrolled target speaker from overlapping 16 kHz speech while preserving the original audio timeline.

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ModelHugging Face

FlashSR

FlashSR is a 2MB audio super-resolution model based on the HierSpeech++'s upsampler architecture. It upscales 16kHz audio to 48kHz at speeds ranging from 200x to 400x real-time.

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ModelHugging Face

ControlNet Uncanny Simpsons v2 0

These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning. You can find some example images in the following.

ControlNetrunwayml/stable-diffusion-v1-5
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ModelHugging Face

Ddpm Celebahq Finetuned Butterflies 2epochs

pipeline = DDPMPipeline.frompretrained('itislulu/ddpm-celebahq-finetuned-butterflies-2epochs') image = pipeline().images[0] image

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ModelHugging Face

EBEN Temple Vibration Pickup

Developed by: Cnam-LMSSC Model: EBEN(M=4,P=1,Q=4) (see publication in IEEE TASLP - arXiv link) Language: French License: MIT Training dataset: speechclean subset of Cnam-LMSSC/vibravox (see VibraVox paper on arXiV)...

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