Trong Vu's picture

Trong Vu

tattrongvu

AI & ML interests

LLM, Reinforcement Learning, Robotics, Self-driving car, Computer Vision

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reacted to openfree's post with 🚀 1 day ago
Datasets Convertor 🚀 https://huggingface.co/spaces/openfree/Datasets-Convertor Welcome to Datasets Convertor, the cutting-edge solution engineered for seamless and efficient data format conversion. Designed with both data professionals and enthusiasts in mind, our tool simplifies the transformation process between CSV, Parquet, and JSONL, XLS file formats, ensuring that your data is always in the right shape for your next analytical or development challenge. 💻✨ Why Choose Datasets Convertor? In today’s data-driven world, managing and converting large datasets can be a daunting task. Our converter is built on top of robust technologies like Pandas and Gradio, delivering reliable performance with a modern, intuitive interface. Whether you’re a data scientist, analyst, or developer, Datasets Convertor empowers you to effortlessly switch between formats while maintaining data integrity and optimizing storage. Key Features and Capabilities: CSV ⇆ Parquet Conversion: Easily transform your CSV files into the highly efficient Parquet format and vice versa. Parquet’s columnar storage not only reduces file size but also accelerates query performance—a critical advantage for big data analytics. 🔄📂 CSV to JSONL Conversion: Convert CSV files to JSONL (newline-delimited JSON) to facilitate efficient, line-by-line data processing. This format is particularly useful for streaming data applications, logging systems, and scenarios where incremental data processing is required. Each CSV row is meticulously converted into an individual JSON record, preserving all the metadata and ensuring compatibility with modern data pipelines. 📄➡️📝 Parquet to JSONL Conversion: For those working with Parquet files, our tool offers a streamlined conversion to JSONL. Parquet to XLS Conversion.
updated a collection 4 days ago
VQA_Dataset
updated a collection 4 days ago
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reacted to openfree's post with 🚀 1 day ago
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Datasets Convertor 🚀

openfree/Datasets-Convertor

Welcome to Datasets Convertor, the cutting-edge solution engineered for seamless and efficient data format conversion. Designed with both data professionals and enthusiasts in mind, our tool simplifies the transformation process between CSV, Parquet, and JSONL, XLS file formats, ensuring that your data is always in the right shape for your next analytical or development challenge. 💻✨

Why Choose Datasets Convertor?
In today’s data-driven world, managing and converting large datasets can be a daunting task. Our converter is built on top of robust technologies like Pandas and Gradio, delivering reliable performance with a modern, intuitive interface. Whether you’re a data scientist, analyst, or developer, Datasets Convertor empowers you to effortlessly switch between formats while maintaining data integrity and optimizing storage.

Key Features and Capabilities:
CSV ⇆ Parquet Conversion:
Easily transform your CSV files into the highly efficient Parquet format and vice versa. Parquet’s columnar storage not only reduces file size but also accelerates query performance—a critical advantage for big data analytics. 🔄📂

CSV to JSONL Conversion:
Convert CSV files to JSONL (newline-delimited JSON) to facilitate efficient, line-by-line data processing. This format is particularly useful for streaming data applications, logging systems, and scenarios where incremental data processing is required. Each CSV row is meticulously converted into an individual JSON record, preserving all the metadata and ensuring compatibility with modern data pipelines. 📄➡️📝

Parquet to JSONL Conversion:
For those working with Parquet files, our tool offers a streamlined conversion to JSONL.

Parquet to XLS Conversion.
New activity in tsystems/colqwen2-7b-v1.0 22 days ago
New activity in tsystems/colqwen2-2b-v1.0-merged 22 days ago
New activity in tsystems/colqwen2-2b-v1.0 22 days ago
New activity in tsystems/colqwen2-7b-v1.0-merged 22 days ago
upvoted an article 23 days ago
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Great explanation ;)
I'm considering between the Slerp and Passthrough to create a smaller version of a big one and use that as speculative draft model.

With Passthrough, would it make sense to pick the layer evenly to avoid too far distance in between layer? (as mentioned in the Solar paper) e.g: original layer from 1 to 10, then pick 1,4,7,10 to create a 2 time smaller model.

Which method would you recommend?
Thanks in advance!

reacted to lewtun's post with 🔥 about 1 month ago
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We are reproducing the full DeepSeek R1 data and training pipeline so everybody can use their recipe. Instead of doing it in secret we can do it together in the open!

🧪 Step 1: replicate the R1-Distill models by distilling a high-quality reasoning corpus from DeepSeek-R1.

🧠 Step 2: replicate the pure RL pipeline that DeepSeek used to create R1-Zero. This will involve curating new, large-scale datasets for math, reasoning, and code.

🔥 Step 3: show we can go from base model -> SFT -> RL via multi-stage training.

Follow along: https://github.com/huggingface/open-r1
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