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appvoid

appvoid

AI & ML interests

training small language models aiming to high-quality text | fine-tuning + merging expert

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updated a collection 5 days ago
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liked a dataset 5 days ago
pszemraj/simple_wikipedia
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appvoid's activity

reacted to victor's post with ❤️ 6 days ago
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3881
Hey everyone, we've given https://hf.co/spaces page a fresh update!

Smart Search: Now just type what you want to do—like "make a viral meme" or "generate music"—and our search gets it.

New Categories: Check out the cool new filter bar with icons to help you pick a category fast.

Redesigned Space Cards: Reworked a bit to really show off the app descriptions, so you know what each Space does at a glance.

Random Prompt: Need ideas? Hit the dice button for a burst of inspiration.

We’d love to hear what you think—drop us some feedback plz!
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reacted to lamhieu's post with 👍 17 days ago
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2221
🚀 Unlock the power of a completely free, unlimited multilingual API!
🌐 The Lightweight Embeddings API offers state-of-the-art text and image embeddings, advanced reranking, and seamless support for over 100 languages — no limits, no restrictions.
🌟 Try it now: lamhieu/lightweight-embeddings
reacted to KnutJaegersberg's post with 👍 2 months ago
reacted to alielfilali01's post with 🤗 2 months ago
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3473
Unpopular opinion: Open Source takes courage to do !

Not everyone is brave enough to release what they have done (the way they've done it) to the wild to be judged !
It really requires a high level of "knowing wth are you doing" ! It's kind of a super power !

Cheers to the heroes here who see this!
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reacted to merve's post with 🔥 3 months ago
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5160
OmniVision-968M: a new local VLM for edge devices, fast & small but performant
💨 a new vision language model with 9x less image tokens, super efficient
📖 aligned with DPO for reducing hallucinations
⚡️ Apache 2.0 license 🔥

Demo hf.co/spaces/NexaAIDev/omnivlm-dpo-demo
Model https://huggingface.co/NexaAIDev/omnivision-968M
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reacted to m-ric's post with 🚀 3 months ago
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1637
𝗔𝗻𝗱𝗿𝗼𝗶𝗱𝗟𝗮𝗯: 𝗙𝗶𝗿𝘀𝘁 𝗲𝘃𝗲𝗿 𝘀𝘆𝘀𝘁𝗲𝗺𝗮𝘁𝗶𝗰 𝗯𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸 𝗳𝗼𝗿 𝗔𝗻𝗱𝗿𝗼𝗶𝗱 𝗺𝗼𝗯𝗶𝗹𝗲 𝗮𝗴𝗲𝗻𝘁𝘀 𝘀𝗵𝗼𝘄𝘀 𝘁𝗵𝗮𝘁 𝘀𝗺𝗮𝗹𝗹, 𝗳𝗶𝗻𝗲-𝘁𝘂𝗻𝗲𝗱 𝗼𝗽𝗲𝗻 𝗺𝗼𝗱𝗲𝗹𝘀 𝗰𝗮𝗻 𝗽𝗼𝘄𝗲𝗿 𝗮 𝗝𝗔𝗥𝗩𝗜𝗦 𝘀𝘆𝘀𝘁𝗲𝗺 𝗼𝗻 𝘆𝗼𝘂𝗿 𝘀𝗺𝗮𝗿𝘁𝗽𝗵𝗼𝗻𝗲 📱🔥

A team from Tsinghua University just released AndroidLab, the first systematic framework to evaluate and train Android mobile agents that works with both text-only and multimodal models.

They show that fine-tuning small open-source models can significantly boost performance, matching that of much bigger closed models like GPT-4o.

The team built:

📊 A reproducible benchmark with 138 tasks across 9 apps to evaluate mobile agents systematically

📝📱 A framework supporting both text-only (via XML) and visual (via marked screenshots) interfaces

✅ An instruction dataset of 10.5k operation traces for training mobile agents

Key insights:

- 📈 Fine-tuning improves performance BY A LOT: Open-source model Llama-3.1-8B improves from 2% to 24% success rate after training, nearly reaching GPT-4o performance although it’s much smaller
- ⚙️ Text-only agents match multimodal ones: XML-based agents achieve similar performance to screenshot-based multimodal agents.

Read their paper here 👉 AndroidLab: Training and Systematic Benchmarking of Android Autonomous Agents (2410.24024)
reacted to KnutJaegersberg's post with 🤗 4 months ago
posted an update 4 months ago
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1409
If someone would like to keep pushing the limits of what's possible on cpu while being efficient/fast, here's my un-trained arco model scaled-up to 770m parameters. Consider it a modern gpt-2-large to experiment with
appvoid/arco-plus
replied to their post 5 months ago
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How long did it take to reply and what are your context window limits? Model type?

it takes 3-5 seconds to reply when the prompt is longer than 30-50 words on average but it increases linearly with number of tokens in the prompt, the one on the picture is llama 3 1b but the one i'm using right now is arco 2 which is a llama model, cannot keep any kind of general knowledge, i noticed with qwen 2 (and later confirmed with meta's model) that you don't need a lot of parameters to get general knowledge, you just need tons of data

posted an update 5 months ago
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3439
700m parameters are the sweet spot for cpu usage, please let's make more of those!
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posted an update 5 months ago
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1825
meta just released 1b parameters model and to honor it i released arco 2 just in time for the fine-tuners to tweak around, enjoy these small powerful language models!!!

meta-llama/Llama-3.2-1B
appvoid/arco-2
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posted an update 5 months ago
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761
WHY ARE THERE NOT TEXT FEWSHOT DATASETS @ HUGGINGFACE? 😲
reacted to zolicsaki's post with 🔥 5 months ago
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1307
Fast inference is no longer a nice-to-have demo; it will be the driving force behind future frontier models. Time to switch over to custom AI hardware and short Nvidia.

Try out SambaNova's lightning fast API for free at https://sambanova.ai/fast-api?api_ref=444868
reacted to KnutJaegersberg's post with ❤️ 5 months ago
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1176
appvoid/arco

arco consistently outperforms every sota model below 600m parameters on average

appvoid/arco
posted an update 6 months ago
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1284
i just made the best 0.5b model to date (again)

its name is arco and is ready to fight any 0.5b model at arc challenge

appvoid/arco
replied to clem's post 6 months ago
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as a model-tweaker is such a huge relief to know we have hf for years to come

reacted to clem's post with ❤️ 6 months ago
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3829
This isn’t a goal of ours because we have plenty of money in the bank but quite excited to see that @huggingfaceis profitable these days, with 220 team members and most of our platform being free (like model hosting) and open-source for the community!

Especially noteworthy at a time when most AI startups wouldn’t survive a year or two without VC money. Yay!
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reacted to severo's post with 🚀 7 months ago
replied to severo's post 7 months ago
posted an update 7 months ago
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1499
palmer-004 becomes 🔥turbo🔥 now is half the size, twice the speed and the best overall 0.5b language model in huggingface.

appvoid/palmer-004-turbo
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