Post
1315
After today you NEED to know how Deepseek made its magic, check out this thread breaking down the paper: https://x.com/AlexBodner_/status/1883602267317927965
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AlexBodner
posted
an
update
2 days ago
Post
1424
🚀 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
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
AlexBodner
posted
an
update
4 days ago
Post
369
How does Deepseek R1 work?
I was wondering the same, so wrote a thread explaining from scratch everything that you need to know about it!
Breaking down the paper in: https://x.com/AlexBodner_/status/1883602267317927965
I was wondering the same, so wrote a thread explaining from scratch everything that you need to know about it!
Breaking down the paper in: https://x.com/AlexBodner_/status/1883602267317927965
AlexBodner
posted
an
update
12 days ago
Post
1473
I just dropped a detailed guide on deploying ML models to Google Cloud Run with GPU support—completely serverless and auto-scaling. If you’re curious about seamlessly deploying your models to the cloud, give it a read! [https://medium.com/@alexbodner/deployment-of-serverless-machine-learning-models-with-gpus-using-google-cloud-cloud-run-573b836475b5]"
- 1 reply
AlexBodner
posted
an
update
20 days ago
Post
1480
Just published a post explaining Monte Carlo Tree Search: the magic behind AlphaZero and now used to tackle reasoning benchmarks with LLMs. Check it out because it's a must know nowadays!
https://x.com/AlexBodner_/status/1877789879398244382
https://x.com/AlexBodner_/status/1877789879398244382
- 1 reply
AlexBodner
posted
an
update
about 1 month ago
Post
474
🚀🤖𝐃𝐨 𝐀𝐧𝐝𝐫𝐨𝐢𝐝𝐬 𝐃𝐫𝐞𝐚𝐦 𝐨𝐟 𝐄𝐥𝐞𝐜𝐭𝐫𝐢𝐜 𝐌𝐚𝐫𝐢𝐨𝐬?
Discover how we replaced the classic game engine with DIAMOND, a Neural Network that predicts every frame based on actions, noise, and past states. From training on human and RL gameplay to generating surreal hallucinations, this project shows the potential of diffusion models in creating amazing simulations. 🎮
🧵 Dive into the full story in our Twitter thread:
👉 https://x.com/AlexBodner_/status/1871566560512643567
🌟 Don’t forget to follow and leave a star for more groundbreaking AI projects!
rmayormartins
updated
a
collection
2 months ago
Español: Accento Costa Rica
1
#1 opened 3 months ago
by
marlhex
Post
1879
🚀 Exploring Topic Modeling with BERTopic 🤖
When you come across an interesting dataset, you often wonder:
Which topics frequently appear in these documents? 🤔
What is this data really about? 📊
Topic modeling helps answer these questions by identifying recurring themes within a collection of documents. This process enables quick and efficient exploratory data analysis.
I’ve been working on an app that leverages BERTopic, a flexible framework designed for topic modeling. Its modularity makes BERTopic powerful, allowing you to switch components with your preferred algorithms. It also supports handling large datasets efficiently by merging models using the BERTopic.merge_models approach. 🔗
🔍 How do we make this work?
Here’s the stack we’re using:
📂 Data Source ➡️ Hugging Face datasets with DuckDB for retrieval
🧠 Text Embeddings ➡️ Sentence Transformers (all-MiniLM-L6-v2)
⚡ Dimensionality Reduction ➡️ RAPIDS cuML UMAP for GPU-accelerated performance
🔍 Clustering ➡️ RAPIDS cuML HDBSCAN for fast clustering
✂️ Tokenization ➡️ CountVectorizer
🔧 Representation Tuning ➡️ KeyBERTInspired + Hugging Face Inference Client with Meta-Llama-3-8B-Instruct
🌍 Visualization ➡️ Datamapplot library
Check out the space and see how you can quickly generate topics from your dataset: datasets-topics/topics-generator
Powered by @MaartenGr - BERTopic
When you come across an interesting dataset, you often wonder:
Which topics frequently appear in these documents? 🤔
What is this data really about? 📊
Topic modeling helps answer these questions by identifying recurring themes within a collection of documents. This process enables quick and efficient exploratory data analysis.
I’ve been working on an app that leverages BERTopic, a flexible framework designed for topic modeling. Its modularity makes BERTopic powerful, allowing you to switch components with your preferred algorithms. It also supports handling large datasets efficiently by merging models using the BERTopic.merge_models approach. 🔗
🔍 How do we make this work?
Here’s the stack we’re using:
📂 Data Source ➡️ Hugging Face datasets with DuckDB for retrieval
🧠 Text Embeddings ➡️ Sentence Transformers (all-MiniLM-L6-v2)
⚡ Dimensionality Reduction ➡️ RAPIDS cuML UMAP for GPU-accelerated performance
🔍 Clustering ➡️ RAPIDS cuML HDBSCAN for fast clustering
✂️ Tokenization ➡️ CountVectorizer
🔧 Representation Tuning ➡️ KeyBERTInspired + Hugging Face Inference Client with Meta-Llama-3-8B-Instruct
🌍 Visualization ➡️ Datamapplot library
Check out the space and see how you can quickly generate topics from your dataset: datasets-topics/topics-generator
Powered by @MaartenGr - BERTopic
AlexBodner
posted
an
update
3 months ago
Post
2405
💾🧠How much VRAM will you need for training your AI model? 💾🧠
Check out this app where you convert:
Pytorch/tensorflow summary -> required VRAM
or
Parameter count -> required VRAM
Use it in: http://howmuchvram.com
And everything is open source! Ask for new functionalities or contribute in:
https://github.com/AlexBodner/How_Much_VRAM
If it's useful to you leave a star 🌟and share it to someone that will find the tool useful!
Check out this app where you convert:
Pytorch/tensorflow summary -> required VRAM
or
Parameter count -> required VRAM
Use it in: http://howmuchvram.com
And everything is open source! Ask for new functionalities or contribute in:
https://github.com/AlexBodner/How_Much_VRAM
If it's useful to you leave a star 🌟and share it to someone that will find the tool useful!
- 1 reply
Post
1280
Multilingual Audio Podcast Generator - Gemma 2 + Edge-TTS
Hello Friends, I want to share my latest kaggle notebook to create a podcast of papers (or any pdf) in more than 21 languages. Implements any LLM (use Gemma2-9b-it) and for the TTS edge-tts. I hope it will be useful for you to catch up with the papers that are coming out faster and faster every day!
https://www.kaggle.com/code/eugeniokukes/multilingual-audio-podcast-generator-gemma-tts
Hello Friends, I want to share my latest kaggle notebook to create a podcast of papers (or any pdf) in more than 21 languages. Implements any LLM (use Gemma2-9b-it) and for the TTS edge-tts. I hope it will be useful for you to catch up with the papers that are coming out faster and faster every day!
https://www.kaggle.com/code/eugeniokukes/multilingual-audio-podcast-generator-gemma-tts
- 1 reply
mariagrandury
authored
a
paper
4 months ago
Post
2561
📝 I wrote a tutorial on how to get started with the fine-tuning process using Hugging Face tools, providing an end-to-end workflow.
The tutorial covers creating a new dataset using the new SQL Console 🛢 and fine-tuning a model with SFT, guided by the Notebook Creator App 📙.
👉 You can read the full article here:
https://huggingface.co/blog/asoria/easy-fine-tuning-with-hf
asoria/auto-notebook-creator
The tutorial covers creating a new dataset using the new SQL Console 🛢 and fine-tuning a model with SFT, guided by the Notebook Creator App 📙.
👉 You can read the full article here:
https://huggingface.co/blog/asoria/easy-fine-tuning-with-hf
asoria/auto-notebook-creator
Post
962
🚀 Excited to share the latest update to the Notebook Creator Tool!
Now with basic fine-tuning support using Supervised Fine-Tuning! 🎯
How it works:
1️⃣ Choose your Hugging Face dataset and notebook type (SFT)
2️⃣ Automatically generate your training notebook
3️⃣ Start fine-tuning with your data!
Link to the app 👉 https://lnkd.in/e_3nmWrB
💡 Want to contribute with new notebooks? 👉https://lnkd.in/eWcZ92dS
Now with basic fine-tuning support using Supervised Fine-Tuning! 🎯
How it works:
1️⃣ Choose your Hugging Face dataset and notebook type (SFT)
2️⃣ Automatically generate your training notebook
3️⃣ Start fine-tuning with your data!
Link to the app 👉 https://lnkd.in/e_3nmWrB
💡 Want to contribute with new notebooks? 👉https://lnkd.in/eWcZ92dS
AlexBodner
posted
an
update
5 months ago
Post
1615
💾🧠How much VRAM will you need for training your AI model? 💾🧠
Check out this app where you convert:
Pytorch/tensorflow summary -> required VRAM
or
Parameter count -> required VRAM
Use it in: http://howmuchvram.com
And everything is open source! Ask for new functionalities or contribute in:
https://github.com/AlexBodner/How_Much_VRAM
If it's useful to you leave a star 🌟and share it to someone that will find the tool useful!
More discussion in: https://x.com/AlexBodner_/status/1832054850294812679
Check out this app where you convert:
Pytorch/tensorflow summary -> required VRAM
or
Parameter count -> required VRAM
Use it in: http://howmuchvram.com
And everything is open source! Ask for new functionalities or contribute in:
https://github.com/AlexBodner/How_Much_VRAM
If it's useful to you leave a star 🌟and share it to someone that will find the tool useful!
More discussion in: https://x.com/AlexBodner_/status/1832054850294812679
AlexBodner
posted
an
update
5 months ago
Post
1845
💾🧠How much VRAM will you need for training your AI model? 💾🧠
Check out this app where you convert:
Pytorch/tensorflow summary -> required VRAM
or
Parameter count -> required VRAM
Use it in: http://howmuchvram.com
And everything is open source! Ask for new functionalities or contribute in:
https://github.com/AlexBodner/How_Much_VRAM
If it's useful to you leave a star 🌟and share it to someone that will find the tool useful!
More discussion in: https://x.com/AlexBodner_/status/1832054850294812679
Check out this app where you convert:
Pytorch/tensorflow summary -> required VRAM
or
Parameter count -> required VRAM
Use it in: http://howmuchvram.com
And everything is open source! Ask for new functionalities or contribute in:
https://github.com/AlexBodner/How_Much_VRAM
If it's useful to you leave a star 🌟and share it to someone that will find the tool useful!
More discussion in: https://x.com/AlexBodner_/status/1832054850294812679
- 1 reply
AlexBodner
posted
an
update
5 months ago
Post
361
💾🧠How much VRAM will you need for training your AI model? 💾🧠
Check out this app where you convert:
Pytorch/tensorflow summary -> required VRAM
or
Parameter count -> required VRAM
Use it in: http://howmuchvram.com
And everything is open source! Ask for new functionalities or contribute in:
https://github.com/AlexBodner/How_Much_VRAM
If it's useful to you leave a star 🌟and share it to someone that will find the tool useful!
More discussion in: https://x.com/AlexBodner_/status/1832054850294812679
Check out this app where you convert:
Pytorch/tensorflow summary -> required VRAM
or
Parameter count -> required VRAM
Use it in: http://howmuchvram.com
And everything is open source! Ask for new functionalities or contribute in:
https://github.com/AlexBodner/How_Much_VRAM
If it's useful to you leave a star 🌟and share it to someone that will find the tool useful!
More discussion in: https://x.com/AlexBodner_/status/1832054850294812679
Post
823
I've been working on a Space to make it super easy to create notebooks and help users quickly understand and manipulate their data!
With just a few clicks automatically generate notebooks for:
📊 Exploratory Data Analysis
🧠 Text Embeddings
🤖 Retrieval-Augmented Generation (RAG)
✨ Automatic training is coming soon!
Check it out here asoria/auto-notebook-creator
Appreciate any feedback to improve this tool 🤗
With just a few clicks automatically generate notebooks for:
📊 Exploratory Data Analysis
🧠 Text Embeddings
🤖 Retrieval-Augmented Generation (RAG)
✨ Automatic training is coming soon!
Check it out here asoria/auto-notebook-creator
Appreciate any feedback to improve this tool 🤗
AlexBodner
posted
an
update
5 months ago
Post
1269
Do you know how PCA and SVD are related?
I explained it for everyone in this post!
Go and check it out: https://x.com/alexbodner_/status/1798357519678718062?s=46
I explained it for everyone in this post!
Go and check it out: https://x.com/alexbodner_/status/1798357519678718062?s=46
AlexBodner
posted
an
update
5 months ago
Post
3792
💾🧠How much VRAM will you need for training your AI model? 💾🧠
Check out this app where you convert:
Pytorch/tensorflow summary -> needed VRAM
or
Parameter count -> needed VRAM
Use it in: http://howmuchvram.com
And everything is open source! Ask for new functionalities or contribute in:
https://github.com/AlexBodner/How_Much_VRAM
If it's useful to you leave a star 🌟and share it to someone that will find the tool useful!
Check out this app where you convert:
Pytorch/tensorflow summary -> needed VRAM
or
Parameter count -> needed VRAM
Use it in: http://howmuchvram.com
And everything is open source! Ask for new functionalities or contribute in:
https://github.com/AlexBodner/How_Much_VRAM
If it's useful to you leave a star 🌟and share it to someone that will find the tool useful!
-
- 3 replies