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Mert Erbak PRO

merterbak

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NLP and Image Processing

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merterbak's activity

reacted to their post with πŸ”₯ about 8 hours ago
posted an update about 8 hours ago
upvoted an article 1 day ago
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Vision Language Models (Better, Faster, Stronger)

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reacted to merve's post with πŸ”₯ 1 day ago
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2816
VLMS 2025 UPDATE πŸ”₯

We just shipped a blog on everything latest on vision language models, including
πŸ€– GUI agents, agentic VLMs, omni models
πŸ“‘ multimodal RAG
⏯️ video LMs
🀏🏻 smol models
..and more! https://huggingface.co/blog/vlms-2025
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reacted to their post with πŸš€πŸ”₯ 2 days ago
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Seed-Coder released and it's designed for coding tasks, featuring base, instruct, and reasoning variants at an 8B parameter scale developed by ByteDance Seed team. Unlike traditional open source LLMs that rely on human crafted rules or annotated data for curating code pretraining datasets Seed-Coder introduces a model-centric data pipeline. The pipeline processes raw data from GitHub and web archives into four categories: file-level codes, repository-level codes, GitHub commits, and code-related web data.A quality filter LLM, evaluates code (for readability, modularity, clarity, and reusability) by removing the lowest 10% to create a 6 trillion token dataset supporting 89 programming languages.
Models: ByteDance-Seed/seed-coder-680de32c15ead6555c75b0e4
Github: https://github.com/ByteDance-Seed/Seed-Coder/tree/master
Paper: https://github.com/ByteDance-Seed/Seed-Coder/blob/master/Seed-Coder.pdf
posted an update 2 days ago
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2047
Seed-Coder released and it's designed for coding tasks, featuring base, instruct, and reasoning variants at an 8B parameter scale developed by ByteDance Seed team. Unlike traditional open source LLMs that rely on human crafted rules or annotated data for curating code pretraining datasets Seed-Coder introduces a model-centric data pipeline. The pipeline processes raw data from GitHub and web archives into four categories: file-level codes, repository-level codes, GitHub commits, and code-related web data.A quality filter LLM, evaluates code (for readability, modularity, clarity, and reusability) by removing the lowest 10% to create a 6 trillion token dataset supporting 89 programming languages.
Models: ByteDance-Seed/seed-coder-680de32c15ead6555c75b0e4
Github: https://github.com/ByteDance-Seed/Seed-Coder/tree/master
Paper: https://github.com/ByteDance-Seed/Seed-Coder/blob/master/Seed-Coder.pdf
reacted to clem's post with πŸ”₯ 5 days ago
reacted to their post with πŸš€πŸ”₯ 12 days ago
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Microsoft released their new fine-tuned phi-4 models with reasoning data yesterday. They outperform/rival much larger models . Check out them if you haven't yet. πŸš€

Phi4 mini reasoning(SFT): microsoft/Phi-4-mini-reasoning
Phi-4 reasoning(SFT): microsoft/Phi-4-reasoning
Phi-4 reasoning plus (SFT + RL): microsoft/Phi-4-reasoning-plus
Demo: https://github.com/marketplace/models/azureml/Phi-4-reasoning/playground
Articles: https://arxiv.org/pdf/2504.21318
https://arxiv.org/pdf/2504.21233
Blog: https://azure.microsoft.com/en-us/blog/one-year-of-phi-small-language-models-making-big-leaps-in-ai/

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posted an update 12 days ago
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Microsoft released their new fine-tuned phi-4 models with reasoning data yesterday. They outperform/rival much larger models . Check out them if you haven't yet. πŸš€

Phi4 mini reasoning(SFT): microsoft/Phi-4-mini-reasoning
Phi-4 reasoning(SFT): microsoft/Phi-4-reasoning
Phi-4 reasoning plus (SFT + RL): microsoft/Phi-4-reasoning-plus
Demo: https://github.com/marketplace/models/azureml/Phi-4-reasoning/playground
Articles: https://arxiv.org/pdf/2504.21318
https://arxiv.org/pdf/2504.21233
Blog: https://azure.microsoft.com/en-us/blog/one-year-of-phi-small-language-models-making-big-leaps-in-ai/

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reacted to clem's post with πŸ€— 12 days ago
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The meta-llama org just crossed 40,000 followers on Hugging Face. Grateful for all their impact on the field sharing the Llama weights openly and much more!

We need more of this from all other big tech to make the AI more open, collaborative and beneficial to all!