North Mini Code Demo
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18
Generate and run Python or web code from a text prompt
Reuben fernandes PRO
Reubencf
AI & ML interests
LLM
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liked a Space about 22 hours ago
CohereLabs/North-Mini-Code-1.0 reacted to theirpost with 🚀 6 days ago
Millions speak Konkani. The internet barely knows it.
Today's major LLMs struggle with regional languages. They can't read, write or even recognize Konkani. So I built one that can.
Here is a working demo of the Konkani LLM I've been training. 👇
https://youtu.be/8K04ylbXh6k
reacted to theirpost with 😎 6 days ago
Millions speak Konkani. The internet barely knows it.
Today's major LLMs struggle with regional languages. They can't read, write or even recognize Konkani. So I built one that can.
Here is a working demo of the Konkani LLM I've been training. 👇
https://youtu.be/8K04ylbXh6k
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liked a
Space about 22 hours ago
reacted to their post with 🚀😎 6 days ago
Post
2033
Millions speak Konkani. The internet barely knows it.
Today's major LLMs struggle with regional languages. They can't read, write or even recognize Konkani. So I built one that can.
Here is a working demo of the Konkani LLM I've been training. 👇
https://youtu.be/8K04ylbXh6k
Today's major LLMs struggle with regional languages. They can't read, write or even recognize Konkani. So I built one that can.
Here is a working demo of the Konkani LLM I've been training. 👇
https://youtu.be/8K04ylbXh6k
reacted to eabdullin's post with 🧠👍 6 days ago
Post
6160
Folks, let me tell you, nobody — and I mean NOBODY — knew transformers before me. People said attention is all you need. I said, "Attention? I INVENTED attention." Everybody's looking at me. Tremendous attention. The best attention scores. My softmax? Perfectly normalized. Other people, sad, their probabilities don't even sum to one. Disaster.
I'm doing a PhD now. A PhD! In Large Language Models. Very large. The largest, believe me. My advisor said, "Sir, your model is overfitting." I said, "Wrong. It's fitting EXACTLY right. It memorized the training set because the training set is fantastic." We don't talk about validation loss in my lab. Validation loss is fake news.
And the internship — oh, the internship. Big tech. I won't say which. Starts with a letter. They BEGGED me. They said, "Please, we need someone who understands gradient descent." I said, "Descent? I only go UP. I'm gradient ASCENT. Loss goes up, that means it's learning to be a winner."
But the GPU cluster — this is the best part. Thousands of H100s. Maybe millions. Who's counting? I'm counting. It's a lot. Other PhD students, they get one little GPU, they're crying, they're training overnight like losers. Me? I burn through compute like nobody's ever seen. The electric company called. They said, "Sir, you've consumed a small country." I said, "Make it a big country. I only do big."
People ask, "Did your model converge?" Folks, it converged so hard. It converged BIGLY. Honestly? My loss curve, it's beautiful, it's going down, down, down — like my approval ratings, very smooth, don't look at the spikes, the spikes are deep state.
And hallucinations? My model doesn't hallucinate. It just has ALTERNATIVE tokens. Thank you, thank you. Tip your reviewers. Accept my paper. Goodnight!
I'm doing a PhD now. A PhD! In Large Language Models. Very large. The largest, believe me. My advisor said, "Sir, your model is overfitting." I said, "Wrong. It's fitting EXACTLY right. It memorized the training set because the training set is fantastic." We don't talk about validation loss in my lab. Validation loss is fake news.
And the internship — oh, the internship. Big tech. I won't say which. Starts with a letter. They BEGGED me. They said, "Please, we need someone who understands gradient descent." I said, "Descent? I only go UP. I'm gradient ASCENT. Loss goes up, that means it's learning to be a winner."
But the GPU cluster — this is the best part. Thousands of H100s. Maybe millions. Who's counting? I'm counting. It's a lot. Other PhD students, they get one little GPU, they're crying, they're training overnight like losers. Me? I burn through compute like nobody's ever seen. The electric company called. They said, "Sir, you've consumed a small country." I said, "Make it a big country. I only do big."
People ask, "Did your model converge?" Folks, it converged so hard. It converged BIGLY. Honestly? My loss curve, it's beautiful, it's going down, down, down — like my approval ratings, very smooth, don't look at the spikes, the spikes are deep state.
And hallucinations? My model doesn't hallucinate. It just has ALTERNATIVE tokens. Thank you, thank you. Tip your reviewers. Accept my paper. Goodnight!
- 16 replies
updated a
Space 6 days ago
posted an update 7 days ago
Post
2033
Millions speak Konkani. The internet barely knows it.
Today's major LLMs struggle with regional languages. They can't read, write or even recognize Konkani. So I built one that can.
Here is a working demo of the Konkani LLM I've been training. 👇
https://youtu.be/8K04ylbXh6k
Today's major LLMs struggle with regional languages. They can't read, write or even recognize Konkani. So I built one that can.
Here is a working demo of the Konkani LLM I've been training. 👇
https://youtu.be/8K04ylbXh6k
huge improvement from opus 4.8 boeing
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#1 opened 7 days ago
by Reubencf
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reacted to Crownelius's post with 🔥 27 days ago
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4681
Howdy,
CompactAI-O is launching a tiny Model Golf, and the winner walks away with $50 in RunPod credits. Monthly. Every month. Show up, build, somebody wins.
What it is
Build the best language model you can under 100 million parameters, with at least a 1028-token context window. That's it. Any architecture, any tokenizer, any training scheme you can dream up at 3am. The only catch is it's gotta be open source (MIT, GPL, Apache, AGPL) take your pick.
It scratches the same itch as a Kaggle comp without the dataset\leaderboard nonsense. No fixed benchmark to game. No llama.cpp compatibility hoops. If you wanna train a 50M-param MoE with five experts and a tokenizer built on cookbooks, you can do that. Nothing stopping you.
The rules are listed in the discord and on the organization page if you're interested.
Why $50????
It's symbolic. It ain't gonna make anyone rich. But it's enough to cover a weekend of GPU time, enough to keep enthusiasts coming back, and not so much that it pulls in people who are just there for the money. Enthusiasts build interesting things. Interesting things move the field forward. A little incentive. I'd do it for $50 lol.
How to join
First round opens soon. Landing page is here:
→ https://huggingface.co/spaces/CompactAI-O/Tiny-model-golf
For questions or to swap ideas, the Discord's open:
→ https://discord.gg/y2jTct6Cxv
Excited to see what yall come up with. ♥
— Shane
CompactAI-O is launching a tiny Model Golf, and the winner walks away with $50 in RunPod credits. Monthly. Every month. Show up, build, somebody wins.
What it is
Build the best language model you can under 100 million parameters, with at least a 1028-token context window. That's it. Any architecture, any tokenizer, any training scheme you can dream up at 3am. The only catch is it's gotta be open source (MIT, GPL, Apache, AGPL) take your pick.
It scratches the same itch as a Kaggle comp without the dataset\leaderboard nonsense. No fixed benchmark to game. No llama.cpp compatibility hoops. If you wanna train a 50M-param MoE with five experts and a tokenizer built on cookbooks, you can do that. Nothing stopping you.
The rules are listed in the discord and on the organization page if you're interested.
Why $50????
It's symbolic. It ain't gonna make anyone rich. But it's enough to cover a weekend of GPU time, enough to keep enthusiasts coming back, and not so much that it pulls in people who are just there for the money. Enthusiasts build interesting things. Interesting things move the field forward. A little incentive. I'd do it for $50 lol.
How to join
First round opens soon. Landing page is here:
→ https://huggingface.co/spaces/CompactAI-O/Tiny-model-golf
For questions or to swap ideas, the Discord's open:
→ https://discord.gg/y2jTct6Cxv
Excited to see what yall come up with. ♥
— Shane
- 8 replies
replied to their post 27 days ago
thanks @Rex1246
replied to their post 27 days ago
thank you very much
upvoted a changelog 28 days ago
Hugging Face Changelog
Filter Leaderboards by Model Size
• 132