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Model statistics of the 50 most downloaded entities on Hugging Face
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ssalvo41
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Model statistics of the 50 most downloaded entities on Hugging Face
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Visualizing How VLMs Work
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reacted to
kadirnar's
post with π₯
2 months ago
Post
2120
What can you do with the VyvoTTS library?
- You can train a model in a language it has never been trained in using the PT model. Thereβs no need for large datasets.
- With the PT model, you can easily replicate the voice of any character you want. Just 1k samples are enough.
- You can add emotion support with a small dataset.
Github: https://github.com/Vyvo-Labs/VyvoTTS
HuggingFace:
Vyvo
- You can train a model in a language it has never been trained in using the PT model. Thereβs no need for large datasets.
- With the PT model, you can easily replicate the voice of any character you want. Just 1k samples are enough.
- You can add emotion support with a small dataset.
Github: https://github.com/Vyvo-Labs/VyvoTTS
HuggingFace:
Vyvo
reacted to
merve's
post with π
5 months ago
Post
3237
Bu post'u Γ§evirebilirsiniz π€π
- 6 replies
reacted to
seawolf2357's
post with π
6 months ago
Post
6488
Samsung Hacking Incident: Samsung Electronics' Official Hugging Face Account Compromised
Samsung Electronics' official Hugging Face account has been hacked. Approximately 17 hours ago, two new language models (LLMs) were registered under Samsung Electronics' official Hugging Face account. These models are:
https://huggingface.co/Samsung/MuTokenZero2-32B
https://huggingface.co/Samsung/MythoMax-L2-13B
The model descriptions contain absurd and false claims, such as being trained on "1 million W200 GPUs," hardware that doesn't even exist.
Moreover, community participants on Hugging Face who have noticed this issue are continuously posting that Samsung Electronics' account has been compromised.
There is concern about potential secondary and tertiary damage if users download these LLMs released under the Samsung Electronics account, trusting Samsung's reputation without knowing about the hack.
Samsung Electronics appears to be unaware of this situation, as they have not taken any visible measures yet, such as changing the account password.
Source: https://discord.gg/openfreeai
Samsung Electronics' official Hugging Face account has been hacked. Approximately 17 hours ago, two new language models (LLMs) were registered under Samsung Electronics' official Hugging Face account. These models are:
https://huggingface.co/Samsung/MuTokenZero2-32B
https://huggingface.co/Samsung/MythoMax-L2-13B
The model descriptions contain absurd and false claims, such as being trained on "1 million W200 GPUs," hardware that doesn't even exist.
Moreover, community participants on Hugging Face who have noticed this issue are continuously posting that Samsung Electronics' account has been compromised.
There is concern about potential secondary and tertiary damage if users download these LLMs released under the Samsung Electronics account, trusting Samsung's reputation without knowing about the hack.
Samsung Electronics appears to be unaware of this situation, as they have not taken any visible measures yet, such as changing the account password.
Source: https://discord.gg/openfreeai
- 2 replies
replied to
ProCreations's
post
6 months ago
Or maybe do a backflip every time a Hugging Face space I want to use gives an error :D
Run with very low VRAM ??
1
#5 opened 6 months ago
by
ssalvo41
reacted to
ProCreations's
post with π
6 months ago
Post
1959
WOULD YOU RATHER
Instantly have 10 of the best GPUs in the world but you can only use/train/tune AI on it
Instantly own all of LLaMA 4 models but your GPU is 10 years old
Or do a backflip every time your AI has an error training (if you are a developer)
Instantly have 10 of the best GPUs in the world but you can only use/train/tune AI on it
Instantly own all of LLaMA 4 models but your GPU is 10 years old
Or do a backflip every time your AI has an error training (if you are a developer)
-
-
- 7 replies
reacted to
albertvillanova's
post with π€
6 months ago
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2868
smolagents v1.14.0 is out! π
π MCPClient: A sleek new client for connecting to remote MCP servers, making integrations more flexible and scalable.
πͺ¨ Amazon Bedrock: Native support for Bedrock-hosted models.
SmolAgents is now more powerful, flexible, and enterprise-ready. πΌ
Full release π https://github.com/huggingface/smolagents/releases/tag/v1.14.0
#smolagents #LLM #AgenticAI
π MCPClient: A sleek new client for connecting to remote MCP servers, making integrations more flexible and scalable.
πͺ¨ Amazon Bedrock: Native support for Bedrock-hosted models.
SmolAgents is now more powerful, flexible, and enterprise-ready. πΌ
Full release π https://github.com/huggingface/smolagents/releases/tag/v1.14.0
#smolagents #LLM #AgenticAI
reacted to
mikonvergence's
post with π§
7 months ago
Post
1692
ππππ ποΈ πππ±π-πππ¬ππ πππ«π«ππ’π§ π ππ§ππ«πππ’π¨π§ π¦π¨πππ₯
MESA is a novel generative model based on latent denoising diffusion capable of generating 2.5D representations (co-registered colour and depth maps) of terrains based on text prompt conditioning.
Work developed by Paul BorneβPons ( @NewtNewt ) during his joint internship at
Adobe & ESA, and in collaboration with asterisk labs.
ποΈ ππ«π¨π£πππ πππ π : https://paulbornep.github.io/mesa-terrain/
π ππ«ππ©π«π’π§π : https://arxiv.org/abs/2504.07210
π€ ππ¨πππ₯ πππ’π π‘ππ¬ : NewtNewt/MESA
πΎ πππππ¬ππ : Major-TOM/Core-DEM
π§π»βπ»βππ¨ππ : https://github.com/PaulBorneP/MESA
ππ ππ©πππ: mikonvergence/MESA
MESA is a novel generative model based on latent denoising diffusion capable of generating 2.5D representations (co-registered colour and depth maps) of terrains based on text prompt conditioning.
Work developed by Paul BorneβPons ( @NewtNewt ) during his joint internship at
Adobe & ESA, and in collaboration with asterisk labs.
ποΈ ππ«π¨π£πππ πππ π : https://paulbornep.github.io/mesa-terrain/
π ππ«ππ©π«π’π§π : https://arxiv.org/abs/2504.07210
π€ ππ¨πππ₯ πππ’π π‘ππ¬ : NewtNewt/MESA
πΎ πππππ¬ππ : Major-TOM/Core-DEM
π§π»βπ»βππ¨ππ : https://github.com/PaulBorneP/MESA
ππ ππ©πππ: mikonvergence/MESA
- 2 replies
reacted to
etemiz's
post with π
7 months ago
Post
2204
It looks like Llama 4 team gamed the LMArena benchmarks by making their Maverick model output emojis, longer responses and ultra high enthusiasm! Is that ethical or not? They could certainly do a better job by working with teams like llama.cpp, just like Qwen team did with Qwen 3 before releasing the model.
In 2024 I started playing with LLMs just before the release of Llama 3. I think Meta contributed a lot to this field and still contributing. Most LLM fine tuning tools are based on their models and also the inference tool llama.cpp has their name on it. The Llama 4 is fast and maybe not the greatest in real performance but still deserves respect. But my enthusiasm towards Llama models is probably because they rank highest on my AHA Leaderboard:
https://sheet.zoho.com/sheet/open/mz41j09cc640a29ba47729fed784a263c1d08
Looks like they did a worse job compared to Llama 3.1 this time. Llama 3.1 has been on top for a while.
Ranking high on my leaderboard is not correlated to technological progress or parameter size. In fact if LLM training is getting away from human alignment thanks to synthetic datasets or something else (?), it could be easily inversely correlated to technological progress. It seems there is a correlation regarding the location of the builders (in the West or East). Western models are ranking higher. This has become more visible as the leaderboard progressed, in the past there was less correlation. And Europeans seem to be in the middle!
Whether you like positive vibes from AI or not, maybe the times are getting closer where humans may be susceptible to being gamed by an AI? What do you think?
In 2024 I started playing with LLMs just before the release of Llama 3. I think Meta contributed a lot to this field and still contributing. Most LLM fine tuning tools are based on their models and also the inference tool llama.cpp has their name on it. The Llama 4 is fast and maybe not the greatest in real performance but still deserves respect. But my enthusiasm towards Llama models is probably because they rank highest on my AHA Leaderboard:
https://sheet.zoho.com/sheet/open/mz41j09cc640a29ba47729fed784a263c1d08
Looks like they did a worse job compared to Llama 3.1 this time. Llama 3.1 has been on top for a while.
Ranking high on my leaderboard is not correlated to technological progress or parameter size. In fact if LLM training is getting away from human alignment thanks to synthetic datasets or something else (?), it could be easily inversely correlated to technological progress. It seems there is a correlation regarding the location of the builders (in the West or East). Western models are ranking higher. This has become more visible as the leaderboard progressed, in the past there was less correlation. And Europeans seem to be in the middle!
Whether you like positive vibes from AI or not, maybe the times are getting closer where humans may be susceptible to being gamed by an AI? What do you think?
- 4 replies
reacted to
merve's
post with π₯
7 months ago
Post
4517
sooo many open AI releases past week, let's summarize! π€
merve/april-11-releases-67fcd78be33d241c0977b9d2
multimodal
> Moonshot AI released Kimi VL Thinking, first working open-source multimodal reasoning model and Kimi VL Instruct, both 16B MoEs with 3B active params (OS)
> InternVL3 released based on Qwen2.5VL, 7 ckpts with various sizes (1B to 78B)
LLMs
> NVIDIA released Llama-3_1-Nemotron-Ultra-253B-v1 an LLM built on Llama 405B for reasoning, chat and tool use
> Agentica released DeepCoder-14B-Preview, fine-tuned version of DeepSeek-R1-Distilled-Qwen-14B on problem-test pairs, along with the compiled dataset
> Zyphra/ZR1-1.5B is a new small reasoning LLM built on R1-Distill-1.5B (OS)
> Skywork-OR1-32B-Preview is a new reasoning model by Skywork
Image Generation
> HiDream releases three new models, HiDream I1 Dev, I1 Full, and I1 fast for image generation (OS)
*OS ones have Apache 2.0 or MIT licenses
merve/april-11-releases-67fcd78be33d241c0977b9d2
multimodal
> Moonshot AI released Kimi VL Thinking, first working open-source multimodal reasoning model and Kimi VL Instruct, both 16B MoEs with 3B active params (OS)
> InternVL3 released based on Qwen2.5VL, 7 ckpts with various sizes (1B to 78B)
LLMs
> NVIDIA released Llama-3_1-Nemotron-Ultra-253B-v1 an LLM built on Llama 405B for reasoning, chat and tool use
> Agentica released DeepCoder-14B-Preview, fine-tuned version of DeepSeek-R1-Distilled-Qwen-14B on problem-test pairs, along with the compiled dataset
> Zyphra/ZR1-1.5B is a new small reasoning LLM built on R1-Distill-1.5B (OS)
> Skywork-OR1-32B-Preview is a new reasoning model by Skywork
Image Generation
> HiDream releases three new models, HiDream I1 Dev, I1 Full, and I1 fast for image generation (OS)
*OS ones have Apache 2.0 or MIT licenses
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-
- 4 replies
OSError: Incorrect path_or_model_id:
2
#16 opened 8 months ago
by
ssalvo41
updated
2
models
10 months ago
updated
2
datasets
10 months ago
updated
3
models
11 months ago