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buttercutter / mlm_original.py
Created November 22, 2024 08:19
Simple masked language modeling code
import torch
import torch.nn as nn
from torch.utils.data import Dataset, DataLoader
from transformers import BertTokenizer, BertForMaskedLM
from datasets import load_dataset
import random
import numpy as np
from tqdm import tqdm
# Set random seed for reproducibility
@buttercutter
buttercutter / article_classify.py
Created November 21, 2024 13:12
Simple code implementation for nlp text clustering and classification tasks
# Credit: Claude-3.5-Sonnet-200k AI chatbot
import numpy as np
from transformers import AutoTokenizer, AutoModel
from transformers import LongformerModel, LongformerTokenizer
import torch
import pandas as pd
import os
import umap
from sklearn.manifold import TSNE
@buttercutter
buttercutter / qosf.py
Created October 31, 2024 06:18
Exercise for qosf
import numpy as np
import matplotlib.pyplot as plt
import time
from qiskit import QuantumCircuit
from qiskit_aer import AerSimulator
from qiskit.quantum_info import Operator
# Define basic quantum gates
def get_X():
return np.array([[0, 1], [1, 0]])
@buttercutter
buttercutter / walk_jump.py
Last active November 29, 2024 09:47
A simple code for [Protein Discovery with Discrete Walk-Jump Sampling](http://arxiv.org/abs/2306.12360)
# Credit : gpt-4o , Claude-3.5-Sonnet-200k , Gemini-Pro-1.5
# Reference :
# [Protein Discovery with Discrete Walk-Jump Sampling](http://arxiv.org/abs/2306.12360)
# [Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion](http://arxiv.org/abs/2407.01392)
import torch
import torch.nn as nn
import torch.nn.functional as F
@buttercutter
buttercutter / cnot_ceviche.py
Last active November 2, 2024 16:49
Some optimization for CNOT gate circuit
import ceviche
import matplotlib.pyplot as plt
import pandas as pd
from skimage.draw import disk as circle
from autograd.scipy.signal import convolve as conv
from scipy.optimize import minimize
from autograd import grad
import autograd.numpy as anp
@buttercutter
buttercutter / nlhf.py
Last active October 31, 2024 21:47
A simple code for [Nash Learning from Human Feedback](http://arxiv.org/abs/2312.00886)
# [Nash Learning from Human Feedback](http://arxiv.org/abs/2312.00886)
import os
import math
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import DataLoader, Dataset
@buttercutter
buttercutter / hqq.py
Created December 31, 2023 10:21
[Half-Quadratic Quantization of Large Machine Learning Models](https://mobiusml.github.io/hqq_blog/)
# Reference: [Half-Quadratic Quantization of Large Machine Learning Models](https://mobiusml.github.io/hqq_blog/)
import numpy as np
# Define the shrinkage function for soft-thresholding
def shrink(x, beta, p):
return np.sign(x) * np.maximum(np.abs(x) - (np.abs(x)**(p-1))/beta, 0)
# Define the quantization and dequantization operators
@buttercutter
buttercutter / mamba.py
Last active May 22, 2024 05:56
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
# [Mamba: Linear-Time Sequence Modeling with Selective State Spaces](https://arxiv.org/abs/2312.00752)
import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import DataLoader, Dataset
from torch.nn import functional as F
from einops import rearrange, repeat
from tqdm import tqdm
@buttercutter
buttercutter / fff.py
Last active November 26, 2023 07:14
A work-in-progress code for [Fast Feedforward Networks](http://arxiv.org/abs/2308.14711)
import torch
from torch import nn
import torch.nn.functional as F
import torchvision
import torchvision.transforms as transforms
from tqdm import tqdm
# Custom fast linear layer
class FastLinear(nn.Module):
def __init__(self, in_features, out_features):
We can't make this file beautiful and searchable because it's too large.
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