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Building interactive demos to scikit-learn examples 🧡

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prithivMLmods 
posted an update about 5 hours ago
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Dropping Downstream tasks using newly initialized parameters and weights ([classifier.bias & weights]) support domain-specific 𝗶𝗺𝗮𝗴𝗲 𝗰𝗹𝗮𝘀𝘀𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻. Based on siglip2-base-patch16-224 and DomainNet (single-domain, multi-source adaptation), with Fashion-MNIST for experimental testing. 🧤☄️

Fashion-Mnist : prithivMLmods/Fashion-Mnist-SigLIP2
Multisource-121 : prithivMLmods/Multisource-121-DomainNet
Painting-126 : prithivMLmods/Painting-126-DomainNet
Sketch-126 : prithivMLmods/Sketch-126-DomainNet
Clipart-126 : prithivMLmods/Clipart-126-DomainNet

Models are trained with different parameter settings for experimental purposes only, with the intent of further development. Refer to the model page below for instructions on running it with Transformers 🤗.

Collection : prithivMLmods/domainnet-exp-67e0e3c934c03cc40c6c8782

Citations : SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features https://arxiv.org/pdf/2502.14786 & Moment Matching for Multi-Source Domain Adaptation : https://arxiv.org/pdf/1812.01754

louisbrulenaudet 
posted an update 1 day ago
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581
I’ve just released logfire-callback on PyPI, designed to facilitate monitoring of Hugging Face Transformer training loops using Pydantic Logfire 🤗

The callback will automatically log training start with configuration parameters, periodic metrics and training completion ⏱️

Install the package using pip:
pip install logfire-callback

First, ensure you have a Logfire API token and set it as an environment variable:
export LOGFIRE_TOKEN=your_logfire_token

Then use the callback in your training code:
from transformers import Trainer, TrainingArguments
from logfire_callback import LogfireCallback

# Initialize your model, dataset, etc.

training_args = TrainingArguments(
    output_dir="./results",
    num_train_epochs=3,
    # ... other training arguments
)

trainer = Trainer(
    model=model,
    args=training_args,
    train_dataset=train_dataset,
    callbacks=[LogfireCallback()]  # Add the Logfire callback here
)

trainer.train()

If you have any feedback, please reach out at @louisbrulenaudet
merve 
posted an update 2 days ago
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2203
So many open releases at Hugging Face past week 🤯 recapping all here ⤵️ merve/march-21-releases-67dbe10e185f199e656140ae

👀 Multimodal
> Mistral AI released a 24B vision LM, both base and instruction FT versions, sota 🔥 (OS)
> with IBM we released SmolDocling, a sota 256M document parser with Apache 2.0 license (OS)
> SpatialLM is a new vision LM that outputs 3D bounding boxes, comes with 0.5B (QwenVL based) and 1B (Llama based) variants
> SkyWork released SkyWork-R1V-38B, new vision reasoning model (OS)

💬 LLMs
> NVIDIA released new Nemotron models in 49B and 8B with their post-training dataset
> LG released EXAONE, new reasoning models in 2.4B, 7.8B and 32B
> Dataset: Glaive AI released a new reasoning dataset of 22M+ examples
> Dataset: NVIDIA released new helpfulness dataset HelpSteer3
> Dataset: OpenManusRL is a new agent dataset based on ReAct framework (OS)
> Open-R1 team released OlympicCoder, new competitive coder model in 7B and 32B
> Dataset: GeneralThought-430K is a new reasoning dataset (OS)

🖼️ Image Generation/Computer Vision
> Roboflow released RF-DETR, new real-time sota object detector (OS) 🔥
> YOLOE is a new real-time zero-shot object detector with text and visual prompts 🥹
> Stability AI released Stable Virtual Camera, a new novel view synthesis model
> Tencent released Hunyuan3D-2mini, new small and fast 3D asset generation model
> ByteDance released InfiniteYou, new realistic photo generation model
> StarVector is a new 8B model that generates svg from images
> FlexWorld is a new model that expands 3D views (OS)

🎤 Audio
> Sesame released CSM-1B new speech generation model (OS)

🤖 Robotics
> NVIDIA released GR00T, new robotics model for generalized reasoning and skills, along with the dataset

*OS ones have Apache 2.0 or MIT license
prithivMLmods 
posted an update 4 days ago
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2139
Play with Orpheus TTS, a Llama-based Speech-LLM designed for high-quality, empathetic text-to-speech generation. This model has been fine-tuned to deliver human-level speech synthesis 🔥🗣️

👉GitHub: https://github.com/PRITHIVSAKTHIUR/Orpheus-TTS-Edge

Demo supporting both text-to-speech and text-to-llm responses in speech.

> voice: tara, dan, emma, josh
> emotion: <laugh>, <chuckle>, <sigh>, <cough>, <sniffle>, <groan>, <yawn>, <gasp>.

🥠Orpheus-3b-0.1-ft
Model Page: canopylabs/orpheus-3b-0.1-ft

🥠Orpheus-3b-0.1-ft
Colab Inference Notebook: https://colab.research.google.com/drive/1KhXT56UePPUHhqitJNUxq63k-pQomz3N?usp=sharing

🥠Finetune [ orpheus-3b-0.1-pretrained ]
Resource: https://github.com/canopyai/Orpheus-TTS/tree/main/finetune

🥠Model-releases:
https://canopylabs.ai/model-releases
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prithivMLmods 
posted an update 10 days ago
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Hey Guys! One Small Announcement 🤗
Stranger Zone now accepts LoRA requests!

✍️Request : strangerzonehf/Request-LoRA [ or ] strangerzonehf/Request-LoRA#1

Page : https://huggingface.co/strangerzonehf

Describe the artistic properties by posting sample images or links to similar images in the request discussion. If the adapters you're asking for are truly creative and safe for work, I'll train and upload the LoRA to the Stranger Zone repo!

Thank you!
prithivMLmods 
posted an update 12 days ago
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Gemma-3-4B : Image and Video Inference 🖼️🎥

🧤Space: prithivMLmods/Gemma-3-Multimodal
🥠Git : https://github.com/PRITHIVSAKTHIUR/Gemma-3-Multimodal

@gemma3 : {Tag + Space_+ 'prompt'}
@video-infer : {Tag + Space_+ 'prompt'}

+ Gemma3-4B : google/gemma-3-4b-it
+ By default, it runs : prithivMLmods/Qwen2-VL-OCR-2B-Instruct

Gemma 3 Technical Report : https://storage.googleapis.com/deepmind-media/gemma/Gemma3Report.pdf
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not-lain 
posted an update 12 days ago
prithivMLmods 
posted an update 13 days ago
Tonic 
posted an update 17 days ago
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1156
🙋🏻‍♂️Hey there folks,

Did you know that you can use ModernBERT to detect model hallucinations ?

Check out the Demo : Tonic/hallucination-test

See here for Medical Context Demo : MultiTransformer/tonic-discharge-guard

check out the model from KRLabs : KRLabsOrg/lettucedect-large-modernbert-en-v1

and the library they kindly open sourced for it : https://github.com/KRLabsOrg/LettuceDetect

👆🏻if you like this topic please contribute code upstream 🚀

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ZennyKenny 
posted an update 19 days ago
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It took me a while, but I've finally got it working: ZennyKenny/note-to-text

Using a Meta LLaMa checkpoint from Unsloth and some help from the HF community, you can capture handwritten notes and convert them into digital format in just a few second.

Really exciting times for AI builders on Hugging Face.
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Tonic 
posted an update 19 days ago
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Powered by KRLabsOrg/lettucedect-large-modernbert-en-v1 from KRLabsOrg.

Detect hallucinations in answers based on context and questions using ModernBERT with 8192-token context support!

### Model Details
- **Model Name**: [lettucedect-large-modernbert-en-v1]( KRLabsOrg/lettucedect-large-modernbert-en-v1)
- **Organization**: [KRLabsOrg](https://huggingface.co/KRLabsOrg)
- **Github**: [https://github.com/KRLabsOrg/LettuceDetect](https://github.com/KRLabsOrg/LettuceDetect)
- **Architecture**: ModernBERT (Large) with extended context support up to 8192 tokens
- **Task**: Token Classification / Hallucination Detection
- **Training Dataset**: [RagTruth]( wandb/RAGTruth-processed)
- **Language**: English
- **Capabilities**: Detects hallucinated spans in answers, provides confidence scores, and calculates average confidence across detected spans.

LettuceDetect excels at processing long documents to determine if an answer aligns with the provided context, making it a powerful tool for ensuring factual accuracy.
prithivMLmods 
posted an update 19 days ago
ZennyKenny 
posted an update 24 days ago
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1884
I've spent most of time working with AI on user-facing apps like Chatbots and TextGen, but today I decided to work on something that I think has a lot of applications for Data Science teams: ZennyKenny/comment_classification

This Space supports uploading a user CSV and categorizing the fields based on user-defined categories. The applications of AI in production are truly endless. 🚀
prithivMLmods 
posted an update 27 days ago
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5863
Dropping some of the custom fine-tunes based on SigLIP2,
with a single/multi label classification problem type! 🌀🧤

- AI vs Deepfake vs Real : prithivMLmods/AI-vs-Deepfake-vs-Real-Siglip2
- Deepfake Detect : prithivMLmods/Deepfake-Detect-Siglip2
- Fire Detection : prithivMLmods/Fire-Detection-Siglip2
- Deepfake Quality Assess : prithivMLmods/Deepfake-Quality-Assess-Siglip2
- Guard Against Unsafe Content : prithivMLmods/Guard-Against-Unsafe-Content-Siglip2

🌠Collection : prithivMLmods/siglip2-custom-67bcdb2de8fe96b99fb4e19e
suayptalha 
posted an update 29 days ago
prithivMLmods 
posted an update about 1 month ago
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It's really interesting about the deployment of a new state of matter in Majorana 1: the world’s first quantum processor powered by topological qubits. If you missed this news this week, here are some links for you:

🅱️Topological qubit arrays: https://arxiv.org/pdf/2502.12252

⚛️ Quantum Blog: https://azure.microsoft.com/en-us/blog/quantum/2025/02/19/microsoft-unveils-majorana-1-the-worlds-first-quantum-processor-powered-by-topological-qubits/

📖 Read the story: https://news.microsoft.com/source/features/innovation/microsofts-majorana-1-chip-carves-new-path-for-quantum-computing/

📝 Majorana 1 Intro: https://youtu.be/Q4xCR20Dh1E?si=Z51DbEYnZFp_88Xp

🌀The Path to a Million Qubits: https://youtu.be/wSHmygPQukQ?si=TS80EhI62oWiMSHK
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merve 
posted an update about 1 month ago
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Google just released PaliGemma 2 Mix: new versatile instruction vision language models 🔥

> Three new models: 3B, 10B, 28B with res 224, 448 💙
> Can do vision language tasks with open-ended prompts, understand documents, and segment or detect anything 🤯

Read more https://huggingface.co/blog/paligemma2mix
Try the demo google/paligemma2-10b-mix
All models are here google/paligemma-2-mix-67ac6a251aaf3ee73679dcc4
prithivMLmods 
posted an update about 1 month ago
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Dino: The Minimalist Multipurpose Chat System 🌠
Agent-Dino : prithivMLmods/Agent-Dino
Github: https://github.com/PRITHIVSAKTHIUR/Agent-Dino

By default, it performs the following tasks:
{Text-to-Text Generation}, {Image-Text-Text Generation}
@image: Generates an image using Stable Diffusion xL.
@3d: Generates a 3D mesh.
@web: Web search agents.
@rAgent: Initiates a reasoning chain using Llama mode for coding explanations.
@tts1-♀, @tts2-♂: Voice generation (Female and Male voices).
@yolo : Object Detection
ZennyKenny 
posted an update about 1 month ago
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2206
Really excited to start contributing to the SWE Arena project: https://swe-arena.com/

Led by IBM PhD fellow @terryyz , our goal is to advance research in code generation and app development by frontier LLMs.

ZennyKenny 
posted an update about 1 month ago
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Okay this is pretty crazy. Snowflake has CortexAI and Uber is already teasing QueryGPT, both of which prominently feature plain text to SQL features to query your database.

I decided to see how hard it would be to put together something similar using 🤗 smolagents. Turns out, it was pretty straightforward. I managed to get it done in London Luton airport this afternoon.

ZennyKenny/sqlAgent
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