Voxel51/GMNCSA24-FO
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Voxel51
company
Verified
AI & ML interests
Visual AI, Computer vision, Multimodal AI, Data Centric AI
Recent Activity
Voxel51's activity
harpreetsahota
updated
a
dataset
2 days ago
pjramg
updated
a
dataset
3 days ago
pjramg
updated
a
dataset
17 days ago
harpreetsahota
updated
a
dataset
17 days ago
Added information about splits and provided metadata
#2 opened about 1 month ago
by
dbogdollumich
TheSteve0
updated
2
datasets
about 1 month ago
Post
2029
🎉 SUPER BLACK FRIDAY DEAL 🎉
Train almost any model on a variety of tasks such as llm finetuning, text classification/regression, summarization, question answering, image classification/regression, object detection, tabular data, etc for FREE using AutoTrain locally. 🔥
https://github.com/huggingface/autotrain-advanced
Train almost any model on a variety of tasks such as llm finetuning, text classification/regression, summarization, question answering, image classification/regression, object detection, tabular data, etc for FREE using AutoTrain locally. 🔥
https://github.com/huggingface/autotrain-advanced
Post
5882
INTRODUCING Hugging Face AutoTrain Client 🔥
Fine-tuning models got even easier!!!!
Now you can fine-tune SOTA models on all compatible dataset-model pairs on Hugging Face Hub using Python on Hugging Face Servers. Choose from a number of GPU flavors, millions of models and dataset pairs and 10+ tasks 🤗
To try, install autotrain-advanced using pip. You can ignore dependencies and install without --no-deps and then you'd need to install some dependencies by hand.
"pip install autotrain-advanced"
Github repo: https://github.com/huggingface/autotrain-advanced
Fine-tuning models got even easier!!!!
Now you can fine-tune SOTA models on all compatible dataset-model pairs on Hugging Face Hub using Python on Hugging Face Servers. Choose from a number of GPU flavors, millions of models and dataset pairs and 10+ tasks 🤗
To try, install autotrain-advanced using pip. You can ignore dependencies and install without --no-deps and then you'd need to install some dependencies by hand.
"pip install autotrain-advanced"
Github repo: https://github.com/huggingface/autotrain-advanced
- 6 replies
abhishek
authored
a
paper
3 months ago
Post
1860
🚨 NEW TASK ALERT 🚨
Extractive Question Answering: because sometimes generative is not all you need 😉
AutoTrain is the only open-source, no code solution to offer so many tasks across different modalities. Current task count: 23 🚀
Check out the blog post on getting started with this task: https://huggingface.co./blog/abhishek/extractive-qa-autotrain
Extractive Question Answering: because sometimes generative is not all you need 😉
AutoTrain is the only open-source, no code solution to offer so many tasks across different modalities. Current task count: 23 🚀
Check out the blog post on getting started with this task: https://huggingface.co./blog/abhishek/extractive-qa-autotrain
harpreetsahota
posted
an
update
8 months ago
Post
2196
The Coachella of Computer Vision, CVPR, is right around the corner. In anticipation of the conference, I curated a dataset of the papers.
I'll have a technical blog post out tomorrow doing some analysis on the dataset, but I'm so hyped that I wanted to get it out to the community ASAP.
The dataset consists of the following fields:
- An image of the first page of the paper
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Here's how I created the dataset 👇🏼
Generic code for building this dataset can be found [here](https://github.com/harpreetsahota204/CVPR-2024-Papers).
This dataset was built using the following steps:
- Scrape the CVPR 2024 website for accepted papers
- Use DuckDuckGo to search for a link to the paper's abstract on arXiv
- Use arXiv.py (python wrapper for the arXiv API) to extract the abstract and categories, and download the pdf for each paper
- Use pdf2image to save the image of paper's first page
- Use GPT-4o to extract keywords from the abstract
Voxel51/CVPR_2024_Papers
I'll have a technical blog post out tomorrow doing some analysis on the dataset, but I'm so hyped that I wanted to get it out to the community ASAP.
The dataset consists of the following fields:
- An image of the first page of the paper
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title: The title of the paper-
authors_list: The list of authors-
abstract: The abstract of the paper-
arxiv_link: Link to the paper on arXiv-
other_link: Link to the project page, if found-
category_name: The primary category this paper according to [arXiv taxonomy](https://arxiv.org/category_taxonomy)-
all_categories: All categories this paper falls into, according to arXiv taxonomy-
keywords: Extracted using GPT-4oHere's how I created the dataset 👇🏼
Generic code for building this dataset can be found [here](https://github.com/harpreetsahota204/CVPR-2024-Papers).
This dataset was built using the following steps:
- Scrape the CVPR 2024 website for accepted papers
- Use DuckDuckGo to search for a link to the paper's abstract on arXiv
- Use arXiv.py (python wrapper for the arXiv API) to extract the abstract and categories, and download the pdf for each paper
- Use pdf2image to save the image of paper's first page
- Use GPT-4o to extract keywords from the abstract
Voxel51/CVPR_2024_Papers
Post
3321
You can now train/finetune custom sentence transformer embedding models using AutoTrain. Read blog: https://huggingface.co./blog/abhishek/finetune-custom-embeddings-autotrain
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- 2 replies
Post
2939
🚨 NEW TASK ALERT 🚨
🎉 AutoTrain now supports Object Detection! 🎉
Transform your projects with these powerful new features:
🔹 Fine-tune any supported model from the Hugging Face Hub
🔹 Seamless logging with TensorBoard or W&B
🔹 Support for local and hub datasets
🔹 Configurable training for tailored results
🔹 Train locally or leverage Hugging Face Spaces
🔹 Deployment-ready with API inference or Hugging Face endpoints
AutoTrain: https://hf.co/autotrain
🎉 AutoTrain now supports Object Detection! 🎉
Transform your projects with these powerful new features:
🔹 Fine-tune any supported model from the Hugging Face Hub
🔹 Seamless logging with TensorBoard or W&B
🔹 Support for local and hub datasets
🔹 Configurable training for tailored results
🔹 Train locally or leverage Hugging Face Spaces
🔹 Deployment-ready with API inference or Hugging Face endpoints
AutoTrain: https://hf.co/autotrain
Post
3067
🚀🚀🚀🚀 Introducing AutoTrain Configs! 🚀🚀🚀🚀
Now you can train models using yaml config files! 💥 These configs are easy to understand and are not at all overwhelming. So, even a person with almost zero knowledge of machine learning can train state of the art models without writing any code. Check out example configs in the config directory of autotrain-advanced github repo and feel free to share configs by creating a pull request 🤗
Github repo: https://github.com/huggingface/autotrain-advanced
Now you can train models using yaml config files! 💥 These configs are easy to understand and are not at all overwhelming. So, even a person with almost zero knowledge of machine learning can train state of the art models without writing any code. Check out example configs in the config directory of autotrain-advanced github repo and feel free to share configs by creating a pull request 🤗
Github repo: https://github.com/huggingface/autotrain-advanced
- 2 replies
Post
3073
Post
2372
Trained another version of llama3-8b-instruct which beats the base model. This time without losing too many points on gsm8k benchmark. Again, using AutoTrain 💥 pip install autotrain-advanced
Trained model: abhishek/autotrain-llama3-orpo-v2
Trained model: abhishek/autotrain-llama3-orpo-v2
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- 1 reply
Post
3478
With AutoTrain, you can already finetune the latest llama3 models without writing a single line of code. Here's an example finetune of llama3 8b model:
abhishek/autotrain-llama3-no-robots
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- 2 replies