Feb. 10, 2024, 5:01 a.m. | /u/iordanis_

Machine Learning www.reddit.com

It must be really frustrating for many to try and train or fine-tune an open-source model only to fail because of just how complicated it is.

Recently heard a conversation of the huggingface developers on a podcast talking about how they identify and debug the activation to apply normalization to stabilize training of LLMs.



I am curious to know, what kind of problems do you run into while training your models (even non-LLM) and how do you usually solve …

apply conversation debug developers huggingface identify kind machinelearning podcast train training

Research Scholar (Technical Research)

@ Centre for the Governance of AI | Hybrid; Oxford, UK

HPC Engineer (x/f/m) - DACH

@ Meshcapade GmbH | Remote, Germany

Senior Analytics Engineer (Retail)

@ Lightspeed Commerce | Toronto, Ontario, Canada

Data Scientist II, BIA GPS India Operations

@ Bristol Myers Squibb | Hyderabad

Analytics Engineer

@ Bestpass | Remote

Senior Analyst - Data Management

@ Marsh McLennan | Mumbai - Hiranandani