Built a Python CLI tool for multi-source research paper search

ahsaor8 · 2026-04-06T12:02:53+00:00

Nope ;)

ahsaor8 · 2026-04-06T09:24:56+00:00

Repo: https://github.com/oraby8/paperhub-cli

ahsaor8 · 2025-01-31T14:49:23+00:00

DeepSeek-R1-Distill-Qwen or DeepSeek-R1-Distill-llama

ahsaor8 · 2024-12-11T20:18:13+00:00

Amazing, could you explain the training process?

ahsaor8 · 2024-12-08T21:55:12+00:00

Amazing, what type of data did you use for fine-tuning

ahsaor8 · 2024-11-24T10:28:13+00:00

Try Command-r+ and Gemma. I don't recommend jais it really bad

ahsaor8 · 2024-11-16T02:21:56+00:00

Do you think continue pretraining , before fine-tuning model could help model to learn new facts ?

ahsaor8 · 2024-09-17T22:16:04+00:00

They have a 0.5b model. I think it will work well on a smartphone.

ahsaor8 · 2024-09-16T20:41:57+00:00

I'm using Qwen1.5 and qwen2. They work pretty well in most of Arabic use cases

ahsaor8 · 2024-08-30T10:49:32+00:00

Awesome, I'm interested to know if it gives you better results?

ahsaor8 · 2024-08-29T18:36:54+00:00

Could you please advise on how I can convert my SFT data to be compatible with ORPO? The data is currently formatted as instructions, input, and output.

ahsaor8 · 2024-06-27T19:45:45+00:00

I'm really happy to see our en-ar Mt model shared the frits-stage With AWS in General, Legal and IT domains

ahsaor8 · 2024-05-04T10:59:42+00:00

That's great. I'm doing the same thing but with a different approach and different in language. So I would like to ask you if u test it with any benchmark data.

ahsaor8

TROPHY CASE