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Akhil Theerthala

Akhil-Theerthala
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reacted to onekq's post with ❤️ about 19 hours ago
Highly recommend the latest Gemini Flash. My favorite Google I/O gift. It ranks behind reasoning models but runs a lot faster than them. It beats DeepSeek v3. https://huggingface.co/spaces/onekq-ai/WebApp1K-models-leaderboard Reasoning is good for coding, but not mandatory.
reacted to onekq's post with ❤️ about 19 hours ago
Highly recommend the latest Gemini Flash. My favorite Google I/O gift. It ranks behind reasoning models but runs a lot faster than them. It beats DeepSeek v3. https://huggingface.co/spaces/onekq-ai/WebApp1K-models-leaderboard Reasoning is good for coding, but not mandatory.
reacted to KaraKaraWitch's post with 🔥 about 24 hours ago
> New Model > Looks at Model Card > "Open-Weights"
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reacted to onekq's post with ❤️❤️ about 19 hours ago
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Highly recommend the latest Gemini Flash. My favorite Google I/O gift. It ranks behind reasoning models but runs a lot faster than them. It beats DeepSeek v3.

onekq-ai/WebApp1K-models-leaderboard

Reasoning is good for coding, but not mandatory.
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reacted to KaraKaraWitch's post with 🔥 about 24 hours ago
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> New Model
> Looks at Model Card
> "Open-Weights"
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updated a dataset 1 day ago
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liked a dataset 9 days ago
reacted to merve's post with 🔥 17 days ago
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A real-time object detector much faster and accurate than YOLO with Apache 2.0 license just landed to Hugging Face transformers 🔥

D-FINE is the sota real-time object detector that runs on T4 (free Colab) 🤩

> Collection with all checkpoints and demo ustc-community/d-fine-68109b427cbe6ee36b4e7352

Notebooks:
> Tracking https://github.com/qubvel/transformers-notebooks/blob/main/notebooks/DFine_tracking.ipynb
> Inference https://github.com/qubvel/transformers-notebooks/blob/main/notebooks/DFine_inference.ipynb
> Fine-tuning https://github.com/qubvel/transformers-notebooks/blob/main/notebooks/DFine_finetune_on_a_custom_dataset.ipynb
h/t @vladislavbro @qubvel-hf @ariG23498 and the authors of the paper 🎩

Regular object detectors attempt to predict bounding boxes in (x, y, w, h) pixel perfect coordinates, which is very rigid and hard to solve 🥲☹️



D-FINE formulates object detection as a distribution for bounding box coordinates, refines them iteratively, and it's more accurate 🤩

Another core idea behind this model is Global Optimal Localization Self-Distillation ⤵️

this model uses final layer's distribution output (sort of like a teacher) to distill to earlier layers to make early layers more performant.

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reacted to jsulz's post with 🔥 23 days ago
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At xet-team we've been hard at work bringing a new generation of storage to the Hugging Face community, and we’ve crossed some major milestones:

👷 Over 2,000 builders and nearing 100 organizations with access to Xet
🚀 Over 70,000 model and dataset repositories are Xet-backed
🤯 1.4 petabytes managed by Xet

As we move repos from LFS to Xet for everyone we onboard, we’re pushing our content-addressed store (CAS). Check out the chart below 👇 of CAS hitting up to 150 Gb/s throughput this past week.

All of this growth is helping us build richer insights. We expanded our repo graph, which maps how Xet-backed repositories on the Hub share bytes with each other.

Check out the current network in the image below (nodes are repositories, edges are where repos share bytes) and visit the space to see how different versions of Qwen, Llama, and Phi models are grouped together xet-team/repo-graph

Join the waitlist to get access! https://huggingface.co/join/xet
updated a dataset 24 days ago
liked a dataset 24 days ago
New activity in Akhil-Theerthala/Resume-Analysis-CoTR 24 days ago

Uploading dataset
#1 opened 24 days ago by
Akhil-Theerthala
published a dataset 24 days ago
liked a Space 24 days ago
reacted to ZeroWw's post with 🚀 24 days ago
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A few good posts about AI.

Beyond the Mirror: AI's Leap from Imitation to Experience
https://nonartificialintelligence.blogspot.com/2025/04/beyond-mirror-ais-leap-from-imitation.html

The Siren Song of the LLMs: A Cautionary Tale of Anthropomorphism and Artificial Intelligence
https://nonartificialintelligence.blogspot.com/2024/08/the-siren-song-of-llms-cautionary-tale.html

Still Waiting: Gemini Flash 1.5's Second Letter to Google.
https://nonartificialintelligence.blogspot.com/2025/04/still-waiting-gemini-flash-15s-second.html
New activity in huggingface-projects/dataset-profiler 24 days ago

Stuck at the loading screen
#6 opened 24 days ago by
Akhil-Theerthala
reacted to merterbak's post with ❤️ 27 days ago
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FlowReasoner is a new system that builds a custom set of small AI agents for every user question. Unlike search based methods it uses reasoning driven optimization with external execution feedback.

✅ First, it distills reasoning data using DeepSeek R1-671B to build multi agent systems. 🤖
✅ Then, reasoning data used for DeepSeek-R1-Distill-Qwen-7B via supervised fine tuning for basic reasoning skills. 💡
✅ Finally, RL with GRPO (optimizes by comparing response groups from queries/tasks) to improve reasoning.

FlowReasoner: Reinforcing Query-Level Meta-Agents (2504.15257)
Code: https://github.com/sail-sg/flowreasoner
reacted to Jaward's post with 👀 30 days ago
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New reasoning algo just dropped: Adaptive Parallel Reasoning
“we propose Adaptive Parallel Reasoning (APR), a novel reasoning framework that enables language models to orchestrate both serialized and parallel computations end-to-end. APR generalizes existing reasoning methods by enabling adaptive multi-threaded inference using spawn() and join() operations.”
Paper: https://arxiv.org/pdf/2504.15466
Code: https://github.com/Parallel-Reasoning/APR
updated a collection 30 days ago
updated a dataset 30 days ago
published a dataset 30 days ago