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TokisakiKurumi

transZ

TokisakiKurumi2001

AI & ML interests

NLP

Recent Activity

liked a model about 2 months ago

migtissera/Tess-R1-Limerick-Llama-3.1-70B

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transZ's activity

liked a model about 2 months ago

migtissera/Tess-R1-Limerick-Llama-3.1-70B

Updated Nov 6 • 26 • 19

upvoted a collection 2 months ago

LLM Reasoning Papers

Collection

Papers to improve reasoning capabilities of LLMs • 17 items • Updated 4 days ago • 91

liked a dataset 3 months ago

migtissera/Synthia-v1.5-I

Viewer • Updated Sep 30 • 20.7k • 57 • 46

liked a model 3 months ago

amd/AMD-Llama-135m

Text Generation • Updated Oct 9 • 32.3k • 110

upvoted a collection 4 months ago

Phi-3

Collection

Phi-3 family of small language and multi-modal models. Language models are available in short- and long-context lengths. • 26 items • Updated Nov 14 • 536

updated a dataset 6 months ago

transZ/GIO

Viewer • Updated Jul 5 • 2 • 55

liked a Space 6 months ago

Running

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Can You Run It? LLM version

liked a model 7 months ago

Locutusque/TinyMistral-248M

Text Generation • Updated May 9 • 1.38k • 42

upvoted a collection 8 months ago

Granite Code Models

Collection

A series of code models trained by IBM licensed under Apache 2.0 license. We release both the base pretrained and instruct models. • 23 items • Updated 8 days ago • 180

upvoted a collection 9 months ago

Model Merging

Collection

Model Merging is a very popular technique nowadays in LLM. Here is a chronological list of papers on the space that will help you get started with it! • 30 items • Updated Jun 12 • 218

reacted to davanstrien's post with 👍 10 months ago

Post

KTO offers an easier way to preference train LLMs (only 👍👎 ratings are required). As part of #DataIsBetterTogether, I've written a tutorial on creating a preference dataset using Argilla and Spaces.

Using this approach, you can create a dataset that anyone with a Hugging Face account can contribute to 🤯

See an example of the kind of Space you can create following this tutorial here: davanstrien/haiku-preferences

🆕 New tutorial covers:
💬 Generating responses with open models
👥 Collecting human feedback (do you like this model response? Yes/No)
🤖 Preparing a TRL-compatible dataset for training aligned models

Check it out here: https://github.com/huggingface/data-is-better-together/tree/main/kto-preference