ritvik77 (Ritvik Gaur)

posted an update 6 months ago

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435

"The question isn't whether machines can think, but whether they should feel." - Ritvik Gaur

https://claude.ai/public/artifacts/89c041a1-5d09-490a-bb57-cfcc151555ad

posted an update 7 months ago

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579

Advanced Quantization Techniques vs. Parameter Scaling: The Efficiency Frontier in Modern AI. What do you think is future ?

1 reply

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reacted to their post with 🔥 8 months ago

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3351

Hi 🤗HF Community,

I would be incredibly grateful for an opportunity to contribute — in any capacity — and learn alongside researchers here. Is there any possibility I could collaborate or assist with any of your research works ?

I’m happy to support ongoing projects, contribute to data analysis, code, documentation, or anything that adds value.

Thank you for your time and consideration!

Warm regards,
Ritvik Gaur

posted an update 8 months ago

Post

3351

Hi 🤗HF Community,

I would be incredibly grateful for an opportunity to contribute — in any capacity — and learn alongside researchers here. Is there any possibility I could collaborate or assist with any of your research works ?

I’m happy to support ongoing projects, contribute to data analysis, code, documentation, or anything that adds value.

Thank you for your time and consideration!

Warm regards,
Ritvik Gaur

reacted to their post with 👍🤯❤️🤗🚀 8 months ago

Post

2348

ritvik77/ContributionChartHuggingFace
It's Ready!

One feature Hugging Face could really benefit from is a contribution heatmap — a visual dashboard to track user engagement and contributions across models, datasets, and models over the year, similar to GitHub’s contribution graph. Guess what, Clem Delangue mentioned idea about using HF API reference for it and we made it for use.

If you are a Hugging Face user add this Space in your collection and it will give you all stats about your contributions and commits nearly same as GitHub. It's still a prototype and still working on it as a product feature.

5 replies

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replied to aiqtech's post 8 months ago

Hey, there's one problem I was facing that instead of having permission for restricted spaces and models I was bypassing them as you can see in code, we can figure out together if HF can provide some API endpoint particularly for this issue.

replied to their post 8 months ago

Thanks for the info, I'll be working on it.

posted an update 8 months ago

Post

2348

ritvik77/ContributionChartHuggingFace
It's Ready!

One feature Hugging Face could really benefit from is a contribution heatmap — a visual dashboard to track user engagement and contributions across models, datasets, and models over the year, similar to GitHub’s contribution graph. Guess what, Clem Delangue mentioned idea about using HF API reference for it and we made it for use.

If you are a Hugging Face user add this Space in your collection and it will give you all stats about your contributions and commits nearly same as GitHub. It's still a prototype and still working on it as a product feature.

5 replies

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reacted to burtenshaw's post with ❤️ 8 months ago

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3941

The Hugging Face Agents Course now includes three major agent frameworks!

🔗

agents-course

This includes LlamaIndex, LangChain, and our very own smolagents. We've worked to integrate the three frameworks in distinctive ways so that learners can reflect on when and where to use each.

This also means that you can follow the course if you're already familiar with one of these frameworks, and soak up some of the fundamental knowledge in earlier units.

Hopefully, this makes the agents course as open to as many people as possible.

3 replies

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posted an update 9 months ago

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492

Someone remember the Wile E. Coyote from Looney Tunes Show? He did it again but now with fooling a Tesla! This shows the difference of LiDAR vs Camera.

Tesla Autopilot Fails Wile E. Coyote Test, Drives Itself Into Picture of a Road.
For Original Video: https://lnkd.in/g4Qi8fd4

replied to their post 9 months ago

Big Asset Firms and tech Giants will soon get a way to even put some price on open source for money.

reacted to their post with ❤️❤️ 9 months ago

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2521

Big companies are now training huge AI models with tons of data and billions of parameters, and the future seems to be about quantization—making those models smaller by turning big numbers into simpler ones, like going from 32-bit to 8-bit without reducing accuracy by +/- 0.01%. There should be some standard unit of measurement for the ratio of model size reduction to accuracy lost.

What do you all thing about this ?

4 replies

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reacted to nicolay-r's post with 👍 9 months ago

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1596

📢 With the recent release of Gemma-3, If you interested to play with textual chain-of-though, the notebook below is a wrapper over the the model (native transformers inference API) for passing the predefined schema of promps in batching mode.
https://github.com/nicolay-r/nlp-thirdgate/blob/master/tutorials/llm_gemma_3.ipynb

Limitation: schema supports texts only (for now), while gemma-3 is a text+image to text.

Model: google/gemma-3-1b-it
Provider: https://github.com/nicolay-r/nlp-thirdgate/blob/master/llm/transformers_gemma3.py

1 reply

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posted an update 9 months ago

Post

2521

Big companies are now training huge AI models with tons of data and billions of parameters, and the future seems to be about quantization—making those models smaller by turning big numbers into simpler ones, like going from 32-bit to 8-bit without reducing accuracy by +/- 0.01%. There should be some standard unit of measurement for the ratio of model size reduction to accuracy lost.

What do you all thing about this ?

4 replies

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reacted to burtenshaw's post with 👍 9 months ago

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2216

Here’s a notebook to make Gemma reason with GRPO & TRL. I made this whilst prepping the next unit of the reasoning course:

In this notebooks I combine together google’s model with some community tooling

- First, I load the model from the Hugging Face hub with transformers’s latest release for Gemma 3
- I use PEFT and bitsandbytes to get it running on Colab
- Then, I took Will Browns processing and reward functions to make reasoning chains from GSM8k
- Finally, I used TRL’s GRPOTrainer to train the model

Next step is to bring Unsloth AI in, then ship it in the reasoning course. Links to notebook below.

https://colab.research.google.com/drive/1Vkl69ytCS3bvOtV9_stRETMthlQXR4wX?usp=sharing

4 replies

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Ritvik Gaur

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Ritvik Gaur

AI & ML interests

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