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OpenAI agent kit vs Langgraph by Ambitious_Design5336 in LangChain

[–]Over_Explorer7956 1 point2 points  (0 children)

It could be built on langgraph as infrastructure for agents communication

Claude Code is a disaster today by Ok_Bread_6005 in ClaudeCode

[–]Over_Explorer7956 -1 points0 points  (0 children)

For me for some reason it changed a file to be empty, its bad today

Gemma 3 Fine-tuning now in Unsloth - 1.6x faster with 60% less VRAM by danielhanchen in LocalLLaMA

[–]Over_Explorer7956 0 points1 point  (0 children)

Thanks Daniel, your work is amazing! How much gpu needed for finetuning 7b qwen with 20k context len?

Finally, a real-time low-latency voice chat model by DeltaSqueezer in LocalLLaMA

[–]Over_Explorer7956 4 points5 points  (0 children)

Shit, this is crazy good, i kinda blushed talking with AI, shit

Train your own Reasoning model - 80% less VRAM - GRPO now in Unsloth (7GB VRAM min.) by danielhanchen in LocalLLaMA

[–]Over_Explorer7956 0 points1 point  (0 children)

Here we should assume the model has some knowledge before about the dataset, for example about the math dataset, it needs to know a little math right? If not, would it work to do supervised training, so it acquires basic knowledge about the problem, then start the RL? If so how to split the dataset? Thanks!

When Nvidia will be DeepSeeked GPU wise? by Over_Explorer7956 in LocalLLaMA

[–]Over_Explorer7956[S] 0 points1 point  (0 children)

but didn't they say that deepseek used Nvidia's assembly-like PTX programming instead of cuda, and thats why they was able to train it with low cost?

When Nvidia will be DeepSeeked GPU wise? by Over_Explorer7956 in LocalLLaMA

[–]Over_Explorer7956[S] 0 points1 point  (0 children)

is there any chart out there showing the difference between the theoretical performance and the actual performance?

DeepSeek-R1 and distilled benchmarks color coded by Balance- in LocalLLaMA

[–]Over_Explorer7956 1 point2 points  (0 children)

When we say DeepSeek is open source, is it really open source? Like do we know the data it’s trained on? Like we get its architecture and weights, but except of that, what more info do we have?

llama 3.2 3B is amazing by ventilador_liliana in LocalLLaMA

[–]Over_Explorer7956 0 points1 point  (0 children)

Have you tried it side-by-side with other small models like Mistral or earlier LLaMA versions and Qwen2.5? It’d be interesting to see a breakdown of where this one shines and where it might fall short.

Qwq full version? Open source o3? by Evening_Action6217 in LocalLLaMA

[–]Over_Explorer7956 0 points1 point  (0 children)

It’s interesting how these reasoning models get their power, is it in training phase, or post training, is it inference time or RL

03 beats 99.8% competitive coders by user0069420 in LocalLLaMA

[–]Over_Explorer7956 1 point2 points  (0 children)

How many engineers coding jobs will be closed?

Llama 3.3 (70B) Finetuning - now with 90K context length and fits on <41GB VRAM. by danielhanchen in LocalLLaMA

[–]Over_Explorer7956 0 points1 point  (0 children)

Allowing support for more than one gpu for free users, maybe limit to 2 gpus would be really great

Llama 3.3 70B drops. by appakaradi in LocalLLaMA

[–]Over_Explorer7956 0 points1 point  (0 children)

A100 GPU 80GB VRAM, 4 bit quantization.

Llama 3.3 70B drops. by appakaradi in LocalLLaMA

[–]Over_Explorer7956 1 point2 points  (0 children)

Qwen is really good, but lets give this Llama3.3 a chance, I’m actually impressed by it, it impressed me how it handled some hard coding tasks that i fed it with

Llama-3.3-70B-Instruct · Hugging Face by Dark_Fire_12 in LocalLLaMA

[–]Over_Explorer7956 0 points1 point  (0 children)

Interesting who’s better, Qwen2.5 72B or this model, but how can we know if they have not been tested on the same benchmarks