catorch

catorch / grpo_demo.py

Created January 30, 2025 23:10 — forked from willccbb/grpo_demo.py

GRPO Llama-1B

	# train_grpo.py
	import re
	import torch
	from datasets import load_dataset, Dataset
	from transformers import AutoTokenizer, AutoModelForCausalLM
	from peft import LoraConfig
	from trl import GRPOConfig, GRPOTrainer

	# Load and prep dataset

catorch / GeneratorDropdown.tsx

Created October 19, 2023 18:13

Current GeneratorDropdown and GeneratorFormInput components styles with error state

	import React, { ChangeEvent, useState, FC } from 'react';

	interface OptionType {
	value: string;
	label: string;
	}

	interface DropdownProps {
	options: OptionType[];
	value: string;

catorch / gist:8ae4bd49b984b28c8837b4a92f39e51e

Last active April 11, 2023 13:22

	import numpy as np
	import torch
	import torch.nn as nn
	import torch.optim as optim
	from sklearn.model_selection import train_test_split
	from sklearn.metrics import accuracy_score, f1_score, classification_report

	class ELM(nn.Module):
	def __init__(self, input_dim, hidden_dim, output_dim):
	super(ELM, self).__init__()

catorch / gist:e11eae4283db753ff6a9a909070e26b5

Created April 10, 2023 00:22

Short R Requirement

	# Install and load the progress package
	if (!requireNamespace("progress")) install.packages("progress")
	library(progress)

	# Generate datasets with different ticket types and status
	set.seed(456)
	tickets1 <- data.frame(TicketType = sample(c("Type A", "Type B", "Type C", "Type D"), size = 100, replace = TRUE),
	Status = sample(c("Open", "Closed"), size = 10, replace = TRUE))

	set.seed(42)

catorch / financial_projection.ipynb

Created April 9, 2023 20:13

financial_projection.ipynb

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