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Krinal Joshi

krinal
victor's profile picture tegridydev's profile picture 21world's profile picture
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AI & ML interests

NLP, Speech

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reacted to openfree's post with 👍 3 days ago
📚 Multilingual RAG Chatbot with PDF Support Chat naturally with your documents! 🌟 ✨ Key Features: • 🌏 Multilingual Q&A support (English, Korean, etc.) • 📄 Real-time PDF and text file processing • 🔍 Context-aware accurate responses • ⚡ Intuitive Chainlit-powered chat interface 🛠️ Tech Stack: • 💻 Clean, documented open-source code • 🤝 User-friendly Chainlit UI • 📊 Vector database for efficient retrieval • 🔄 Real-time streaming responses 📱 Try it now! → Demo: https://huggingface.co/spaces/openfree/PDF-RAG 🔧 Special Features: • 📊 Support for PDF/text files up to 2MB • 🎯 Precise context understanding • ⚡ Fast response time • 🔒 Secure file handling Full source code available - ready to integrate into your projects! #RAG #NLP #Chatbot #OpenSource #PDFProcessing
reacted to tegridydev's post with 👍 3 days ago
So, what is #MechanisticInterpretability 🤔 Mechanistic Interpretability (MI) is the discipline of opening the black box of large language models (and other neural networks) to understand the underlying circuits, features and/or mechanisms that give rise to specific behaviours Instead of treating a model as a monolithic function, we can: 1. Trace how input tokens propagate through attention heads & MLP layers 2. Identify localized “circuit motifs” 3. Develop methods to systematically break down or “edit” these circuits to confirm we understand the causal structure. Mechanistic Interpretability aims to yield human-understandable explanations of how advanced models represent and manipulate concepts which hopefully leads to 1. Trust & Reliability 2. Safety & Alignment 3. Better Debugging / Development Insights https://bsky.app/profile/mechanistics.bsky.social/post/3lgvvv72uls2x
replied to tegridydev's post 3 days ago
So, what is #MechanisticInterpretability 🤔 Mechanistic Interpretability (MI) is the discipline of opening the black box of large language models (and other neural networks) to understand the underlying circuits, features and/or mechanisms that give rise to specific behaviours Instead of treating a model as a monolithic function, we can: 1. Trace how input tokens propagate through attention heads & MLP layers 2. Identify localized “circuit motifs” 3. Develop methods to systematically break down or “edit” these circuits to confirm we understand the causal structure. Mechanistic Interpretability aims to yield human-understandable explanations of how advanced models represent and manipulate concepts which hopefully leads to 1. Trust & Reliability 2. Safety & Alignment 3. Better Debugging / Development Insights https://bsky.app/profile/mechanistics.bsky.social/post/3lgvvv72uls2x
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krinal's activity

reacted to openfree's post with 👍 3 days ago
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5928
📚 Multilingual RAG Chatbot with PDF Support

Chat naturally with your documents! 🌟

✨ Key Features:
• 🌏 Multilingual Q&A support (English, Korean, etc.)
• 📄 Real-time PDF and text file processing
• 🔍 Context-aware accurate responses
• ⚡ Intuitive Chainlit-powered chat interface

🛠️ Tech Stack:
• 💻 Clean, documented open-source code
• 🤝 User-friendly Chainlit UI
• 📊 Vector database for efficient retrieval
• 🔄 Real-time streaming responses

📱 Try it now!
→ Demo: openfree/PDF-RAG

🔧 Special Features:
• 📊 Support for PDF/text files up to 2MB
• 🎯 Precise context understanding
• ⚡ Fast response time
• 🔒 Secure file handling

Full source code available - ready to integrate into your projects!

#RAG #NLP #Chatbot #OpenSource #PDFProcessing
reacted to tegridydev's post with 👍 3 days ago
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1343
So, what is #MechanisticInterpretability 🤔

Mechanistic Interpretability (MI) is the discipline of opening the black box of large language models (and other neural networks) to understand the underlying circuits, features and/or mechanisms that give rise to specific behaviours

Instead of treating a model as a monolithic function, we can:

1. Trace how input tokens propagate through attention heads & MLP layers
2. Identify localized “circuit motifs”
3. Develop methods to systematically break down or “edit” these circuits to confirm we understand the causal structure.

Mechanistic Interpretability aims to yield human-understandable explanations of how advanced models represent and manipulate concepts which hopefully leads to

1. Trust & Reliability
2. Safety & Alignment
3. Better Debugging / Development Insights

https://bsky.app/profile/mechanistics.bsky.social/post/3lgvvv72uls2x
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replied to tegridydev's post 3 days ago
reacted to hexgrad's post with 👍 3 days ago
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upvoted an article 3 days ago
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Welcome to Inference Providers on the Hub 🔥

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liked a model 6 days ago
reacted to alibabasglab's post with 👍 6 days ago
reacted to mmaguero's post with 👍 6 days ago
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🚀 Multidimensional Affective Analysis for Guarani/Jopara! 🌎

This project explored affective computing for low-resource languages, focusing on emotion recognition, humor detection, and offensive language identification in Guarani and Jopara (a code-switching mix of Guarani and Spanish).

Highlights:
🧵 Corpora:
- Emotion Recognition
- Humor Detection
- Offensive Language Identification
💻 Base Models for Fine-Tuning (trained on Guarani Wiki):
- From scratch: BERT-based tiny, small, base and large models
- Continuously pre-trained models: Multilingual-BERT and BETO
📓 Baseline Notebooks:
- Fine-tuning BERT-based models
- NCRF++ models via GitHub

💡 Check the repo!
https://github.com/mmaguero/guarani-multi-affective-analysis

📖 Check out the publication here:
- https://digibug.ugr.es/handle/10481/98843
- https://link.springer.com/article/10.1007/s12559-023-10165-0

#NLP #AffectiveComputing #LowResourceLanguages #Guarani #Jopara #SentimentAnalysis #AIForAll
reacted to nicolay-r's post with 👍 14 days ago
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📢 So far I been passioned about making NLP pipeline for handling iterator of texts with no-string dependency from besides third-party providers of your choice.

By starting with text-translation, delighted to share the related notebooks that might save you time for handling your data

⭐ https://github.com/nicolay-r/nlp-thirdgate

Example of using GoogleTranslate API in no-string for handling textual data iterators with spans:

📙 https://github.com/nicolay-r/nlp-thirdgate/blob/master/tutorials/translate_texts_with_spans_via_googletrans.ipynb

The key concept is that all these API examples could be tied into a single pipeline using AREkit

📘 https://github.com/nicolay-r/AREkit

🛠️ The further plan is to popualte this repo with
1. NER (DeepPavlov models wrapper)
2. LLM with fancy out-of-the-box chain-of-thought declaration support.
liked a model 14 days ago
upvoted an article 16 days ago
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Article

Train 400x faster Static Embedding Models with Sentence Transformers

• 130
upvoted a paper 17 days ago
reacted to alibabasglab's post with 👍 18 days ago
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2589
We are thrilled to present the improved "ClearerVoice-Studio", an open-source platform designed to make speech processing easy use for everyone! Whether you’re working on speech enhancement, speech separation, speech super-resolution, or target speaker extraction, this unified platform has you covered.

** Why Choose ClearerVoice-Studio?**

- Pre-Trained Models: Includes cutting-edge pre-trained models, fine-tuned on extensive, high-quality datasets. No need to start from scratch!
- Ease of Use: Designed for seamless integration with your projects, offering a simple yet flexible interface for inference and training.

**Where to Find Us?**

- GitHub Repository: ClearerVoice-Studio (https://github.com/modelscope/ClearerVoice-Studio)
- Try Our Demo: Hugging Face Space ( alibabasglab/ClearVoice)

**What Can You Do with ClearerVoice-Studio?**

- Enhance noisy speech recordings to achieve crystal-clear quality.
- Separate speech from complex audio mixtures with ease.
- Transform low-resolution audio into high-resolution audio. A full upscaled LJSpeech-1.1-48kHz dataset can be downloaded from alibabasglab/LJSpeech-1.1-48kHz .
- Extract target speaker voices with precision using audio-visual models.

**Join Us in Growing ClearerVoice-Studio!**

We believe in the power of open-source collaboration. By starring our GitHub repository and sharing ClearerVoice-Studio with your network, you can help us grow this community-driven platform.

**Support us by:**

- Starring it on GitHub.
- Exploring and contributing to our codebase .
- Sharing your feedback and use cases to make the platform even better.
- Joining our community discussions to exchange ideas and innovations.
- Together, let’s push the boundaries of speech processing! Thank you for your support! :sparkling_heart:
reacted to AdinaY's post with 🔥 18 days ago
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3178
MiniCPM-o2.6 🔥 an end-side multimodal LLMs released by OpenBMB from the Chinese community
Model: openbmb/MiniCPM-o-2_6
✨ Real-time English/Chinese conversation, emotion control and ASR/STT
✨ Real-time video/audio understanding
✨ Processes up to 1.8M pixels, leads OCRBench & supports 30+ languages
liked a model 18 days ago
reacted to davidberenstein1957's post with 👍 18 days ago
reacted to lamhieu's post with 👍 18 days ago
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1868
Unlock seamless document conversion with Docsifer, powered by MarkItDown at its core! 🚀 Effortlessly transform PDFs, Word, Excel, images, audio, HTML, and more into clean, structured Markdown—perfect for developers, writers, and content creators. With optional LLM-enhanced extraction and robust format support, Docsifer ensures accuracy, speed, and privacy.
🌟 Try it now and experience professional-grade Markdown conversion: lamhieu/docsifer
upvoted an article 20 days ago
liked a Space 20 days ago