DeepSeek-R1
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8 items
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Updated
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575
Lathashree
lathashree01
AI & ML interests
NLP, Computer Vision, Gen AI for Healthcare
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upvoted
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8 days ago
DeepSeek-R1
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8 days ago
deepseek-ai/DeepSeek-R1
updated
a Space
28 days ago
lathashree01/weather_agent
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lathashree01's activity
upvoted
a
collection
8 days ago
liked
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model
8 days ago
updated
a
Space
28 days ago
Adding `safetensors` variant of this model
#1 opened about 1 month ago
by
SFconvertbot
reacted to
julien-c's
post with 🔥
3 months ago
Post
10350
After some heated discussion 🔥, we clarify our intent re. storage limits on the Hub
TL;DR:
- public storage is free, and (unless blatant abuse) unlimited. We do ask that you consider upgrading to PRO and/or Enterprise Hub if possible
- private storage is paid above a significant free tier (1TB if you have a paid account, 100GB otherwise)
docs: https://huggingface.co/docs/hub/storage-limits
We optimize our infrastructure continuously to scale our storage for the coming years of growth in Machine learning, to the benefit of the community 🔥
cc: @reach-vb @pierric @victor and the HF team
TL;DR:
- public storage is free, and (unless blatant abuse) unlimited. We do ask that you consider upgrading to PRO and/or Enterprise Hub if possible
- private storage is paid above a significant free tier (1TB if you have a paid account, 100GB otherwise)
docs: https://huggingface.co/docs/hub/storage-limits
We optimize our infrastructure continuously to scale our storage for the coming years of growth in Machine learning, to the benefit of the community 🔥
cc: @reach-vb @pierric @victor and the HF team
- 28 replies
liked
a
model
5 months ago
upvoted
an
article
8 months ago
Article
SmolLM - blazingly fast and remarkably powerful
•
333
reacted to
rwightman's
post with 🔥
9 months ago
Post
2459
MobileNetV4 weights are now in timm! So far these are the only weights for these models as the offiicial Tensorflow impl remains weightless.
Guided by paper hparams with a few tweaks, I've managed to match or beat the paper results training the medium models. I'm still working on large and improving the small result. They appear to be solid models for on-device use.
timm/mobilenetv4-pretrained-weights-6669c22cda4db4244def9637
MobileNetV4 -- Universal Models for the Mobile Ecosystem (2404.10518)
Guided by paper hparams with a few tweaks, I've managed to match or beat the paper results training the medium models. I'm still working on large and improving the small result. They appear to be solid models for on-device use.
timm/mobilenetv4-pretrained-weights-6669c22cda4db4244def9637
MobileNetV4 -- Universal Models for the Mobile Ecosystem (2404.10518)
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