Squeeze Beats (CEO Kim Hyeong-jun), a specialist in artificial intelligence (AI) lightweighting and optimization, announced on the third that it has launched 'Matches on Chips', a customized solution for serving large language models (LLM).
Matches...
We are going to use it for example of a straightforward query: we would like to count the variety of users that don’t have Twitter handles.EXPLAIN ANALYZESELECT COUNT(*) FROM users WHERE twitter != '';Let's...
How paying “higher” attention can drive ML cost savingsOnce more, Flex Attention offers a substantial performance boost, amounting to 2.19x in eager mode and a pair of.59x in compiled mode.Flex Attention LimitationsAlthough we've got...
A groundbreaking recent technique, developed by a team of researchers from Meta, UC Berkeley, and NYU, guarantees to reinforce how AI systems approach general tasks. Referred to as “Thought Preference Optimization” (TPO), this method...
Part 3: The algorithm under the hoodUp until now, this series has covered the fundamentals of linear programming. In this text, we're going to move from basic concepts into the main points under the...
There may be a joke that cracks me up:“Did that, before the clock was invented, people needed to actively roam around and ask people the time?”There may be obviously no need to clarify...
import torch
import torch.nn.functional as F
class DPOTrainer:
def __init__(self, model, ref_model, beta=0.1, lr=1e-5):
self.model = model
self.ref_model =...