My latest project is the outcome of the last 2+ years working with TPUs from the amazing TPU Research Cloud (TRC) program and training Encoder-only LMs with the TensorFlow Model Garden library.
- Cheatsheet for setting-up a TPU VM Pod (with all necessary dependencies) to pretrain LMs with TF Model Garden - Conversion scripts that convert TF Model Garden weights to Hugging Face Transformers-compatible models - Supported architectures include BERT, BERT with Token Dropping and TEAMS
I also released BERT-based models pretrained on the great Hugging Face FineWeb and FineWeb-Edu datasets (10BT subset). With more to come!
Increasingly, LLMs are becoming very useful for helping scale annotation tasks, i.e. labelling and filtering. When combined with the structured generation, this can be a very scalable way of doing some pre-annotation without requiring a large team of human annotators.
The Bluesky AT Protocol unlocks exciting possibilities: - Building custom feeds using ML - Creating dashboards for data exploration - Developing custom models for Bluesky To gather Bluesky resources on the Hub, I've created a community org: https://huggingface.co/bluesky-community
My first rather modest contribution is a dashboard that shows the number of posts every second. Drinking straight from the firehose API 🚰
Yesterday, I shared a blog post on generating data for fine-tuning ColPali using the Qwen/Qwen2-VL-7B-Instruct model.
To simplify testing this approach, I created a Space that lets you generate queries from an input document page image: davanstrien/ColPali-Query-Generator
I think there is much room for improvement, but I'm excited about the potential for relatively small VLMs to create synthetic data.
ColPali is revolutionizing multimodal retrieval, but could it be even more effective with domain-specific fine-tuning?
Check out my latest blog post, where I guide you through creating a ColPali fine-tuning dataset using Qwen/Qwen2-VL-7B-Instruct to generate queries for a collection of UFO documents sourced from the Internet Archive.
The post covers: - Introduction to data for ColPali models - Using Qwen2-VL for retrieval query generation - Tips for better query generation
🛸 I'm working on a pipeline for creating domain-specific ColPali fine-tuning datasets using a collection of UFO newsletters from the Internet Archive as a case study.
I will have a full notebook to share on Monday, but you can already take a look at the dataset here: davanstrien/ufo-ColPali