33
MEMO
👁
Memory-Guided Diffusion for Expressive Talking Video Gen
Nikita Davidchuk
Ar4ikov
AI & ML interests
nlp, web, opensource, transformers, asr, ser, tts, cv
Recent Activity
liked
a Space
24 days ago
fffiloni/MEMO
liked
a model
about 1 month ago
yandex/YandexGPT-5-Lite-8B-pretrain
liked
a Space
about 1 month ago
nanotron/ultrascale-playbook
Organizations
Ar4ikov's activity
liked
a
Space
24 days ago
liked
a
model
about 1 month ago
liked
5
Spaces
about 1 month ago
2.35k
The Ultra-Scale Playbook
🌌
The ultimate guide to training LLM on large GPU Clusters
631
Open Deep-Research
🏆
OpenAI's Deep Research, but open
395
OmniParser V2
🏢
OmniParser, turn your LLM into GUI agent
1.19k
LuminaBrush
📈
Execute custom code from environment variable
133
Workflow Canvas
🖼
FLUX Hand-written STYLE Genereator
liked
a
Space
about 2 months ago
liked
2
models
about 2 months ago
liked
a
Space
about 2 months ago
liked
4
models
about 2 months ago
liked
a
model
2 months ago
liked
a
Space
2 months ago
liked
a
model
3 months ago
liked
a
Space
3 months ago
reacted to
suayptalha's
post with ❤️
3 months ago
Post
2151
🚀 Introducing 𝐅𝐢𝐫𝐬𝐭 𝐇𝐮𝐠𝐠𝐢𝐧𝐠 𝐅𝐚𝐜𝐞 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐦𝐢𝐧𝐆𝐑𝐔 𝐌𝐨𝐝𝐞𝐥𝐬 from the paper 𝐖𝐞𝐫𝐞 𝐑𝐍𝐍𝐬 𝐀𝐥𝐥 𝐖𝐞 𝐍𝐞𝐞𝐝𝐞𝐝?
🖥 I have integrated 𝐧𝐞𝐱𝐭-𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 𝐑𝐍𝐍𝐬, specifically minGRU, which offer faster performance compared to Transformer architectures, into HuggingFace. This allows users to leverage the lighter and more efficient minGRU models with the "𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐞𝐫𝐬" 𝐥𝐢𝐛𝐫𝐚𝐫𝐲 for both usage and training.
💻 I integrated two main tasks: 𝐌𝐢𝐧𝐆𝐑𝐔𝐅𝐨𝐫𝐒𝐞𝐪𝐮𝐞𝐧𝐜𝐞𝐂𝐥𝐚𝐬𝐬𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 and 𝐌𝐢𝐧𝐆𝐑𝐔𝐅𝐨𝐫𝐂𝐚𝐮𝐬𝐚𝐥𝐋𝐌.
𝐌𝐢𝐧𝐆𝐑𝐔𝐅𝐨𝐫𝐒𝐞𝐪𝐮𝐞𝐧𝐜𝐞𝐂𝐥𝐚𝐬𝐬𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧:
You can use this class for 𝐒𝐞𝐪𝐮𝐞𝐧𝐜𝐞 𝐂𝐥𝐚𝐬𝐬𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 tasks. I also trained a Sentiment Analysis model with stanfordnlp/imdb dataset.
𝐌𝐢𝐧𝐆𝐑𝐔𝐅𝐨𝐫𝐂𝐚𝐮𝐬𝐚𝐥𝐋𝐌:
You can use this class for 𝐂𝐚𝐮𝐬𝐚𝐥 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐌𝐨𝐝𝐞𝐥 tasks such as GPT, Llama. I also trained an example model with roneneldan/TinyStories dataset. You can fine-tune and use it!
🔗 𝐋𝐢𝐧𝐤𝐬:
Models: suayptalha/mingru-676fe8d90760d01b7955d7ab
GitHub: https://github.com/suayptalha/minGRU-hf
LinkedIn Post: https://www.linkedin.com/posts/suayp-talha-kocabay_mingru-a-suayptalha-collection-activity-7278755484172439552-wNY1
📰 𝐂𝐫𝐞𝐝𝐢𝐭𝐬:
Paper Link: https://arxiv.org/abs/2410.01201
I am thankful to Leo Feng, Frederick Tung, Mohamed Osama Ahmed, Yoshua Bengio and Hossein Hajimirsadeghi for their papers.
🖥 I have integrated 𝐧𝐞𝐱𝐭-𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 𝐑𝐍𝐍𝐬, specifically minGRU, which offer faster performance compared to Transformer architectures, into HuggingFace. This allows users to leverage the lighter and more efficient minGRU models with the "𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐞𝐫𝐬" 𝐥𝐢𝐛𝐫𝐚𝐫𝐲 for both usage and training.
💻 I integrated two main tasks: 𝐌𝐢𝐧𝐆𝐑𝐔𝐅𝐨𝐫𝐒𝐞𝐪𝐮𝐞𝐧𝐜𝐞𝐂𝐥𝐚𝐬𝐬𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 and 𝐌𝐢𝐧𝐆𝐑𝐔𝐅𝐨𝐫𝐂𝐚𝐮𝐬𝐚𝐥𝐋𝐌.
𝐌𝐢𝐧𝐆𝐑𝐔𝐅𝐨𝐫𝐒𝐞𝐪𝐮𝐞𝐧𝐜𝐞𝐂𝐥𝐚𝐬𝐬𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧:
You can use this class for 𝐒𝐞𝐪𝐮𝐞𝐧𝐜𝐞 𝐂𝐥𝐚𝐬𝐬𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 tasks. I also trained a Sentiment Analysis model with stanfordnlp/imdb dataset.
𝐌𝐢𝐧𝐆𝐑𝐔𝐅𝐨𝐫𝐂𝐚𝐮𝐬𝐚𝐥𝐋𝐌:
You can use this class for 𝐂𝐚𝐮𝐬𝐚𝐥 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐌𝐨𝐝𝐞𝐥 tasks such as GPT, Llama. I also trained an example model with roneneldan/TinyStories dataset. You can fine-tune and use it!
🔗 𝐋𝐢𝐧𝐤𝐬:
Models: suayptalha/mingru-676fe8d90760d01b7955d7ab
GitHub: https://github.com/suayptalha/minGRU-hf
LinkedIn Post: https://www.linkedin.com/posts/suayp-talha-kocabay_mingru-a-suayptalha-collection-activity-7278755484172439552-wNY1
📰 𝐂𝐫𝐞𝐝𝐢𝐭𝐬:
Paper Link: https://arxiv.org/abs/2410.01201
I am thankful to Leo Feng, Frederick Tung, Mohamed Osama Ahmed, Yoshua Bengio and Hossein Hajimirsadeghi for their papers.