I hereby claim:
- I am shreyansh26 on github.
- I am shreyansh26 (https://keybase.io/shreyansh26) on keybase.
- I have a public key ASAoslMXqpms4-sn1xknNjBcBKZKk3Erypeh7HONCGuE0go
To claim this, I am signing this object:
import json | |
import sentencepiece as spm | |
import sentencepiece.sentencepiece_model_pb2 as sp_pb2 | |
from google.protobuf.json_format import MessageToDict | |
PATH = "tokenizer.model" | |
s = spm.SentencePieceProcessor(model_file=PATH) |
from transformers import AutoModelForCausalLM, AutoTokenizer | |
tok = AutoTokenizer.from_pretrained("distilgpt2") | |
model = AutoModelForCausalLM.from_pretrained("distilgpt2") | |
inputs = tok(["Hello how"], return_tensors="pt") | |
len_inp = len(inputs.input_ids[0]) | |
print(len_inp) | |
generated = model.generate(**inputs, do_sample=False, max_new_tokens=10) |
import math | |
import torch | |
import torch.nn as nn | |
from torch.nn import functional as F | |
class RelativePositionBias(nn.Module): | |
def __init__(self, bidirectional=True, num_buckets=32, max_distance=128, n_heads=2): | |
super(RelativePositionBias, self).__init__() | |
self.bidirectional = bidirectional |
import numpy as np # import numpy library | |
from util.paramInitializer import initialize_parameters # import function to initialize weights and biases | |
class LinearLayer: | |
""" | |
This Class implements all functions to be executed by a linear layer | |
in a computational graph | |
Args: |
#!/usr/bin/python | |
from z3 import * | |
s = [BitVec("s[%d]" % i,32)for i in range(0,8)] | |
# shouldve | |
z3_solver = Solver() | |
flag = "" | |
for i in range(0,len(s)): |
if(strlen(input) != 23) { | |
print_wrong; | |
return 0; | |
} | |
if((input[4] ^ 0x6c) != 0) { | |
print_wrong; | |
return 0; | |
} | |
if(input[3] + 1 != input[6]) { |
from PIL import Image | |
image_enc = open('encoded_img', 'r').readlines() | |
print(image_enc) | |
pixels = [] | |
for row in image_enc: | |
row = row.strip() | |
row = row.split('+') |
#!/usr/bin/python3 | |
img = bytearray(open('matrix_modified.bmp', 'rb').read()) | |
key = "matrix" | |
new_f = [] | |
for i, x in enumerate(img): | |
new_f.append(hex(ord(key[i%6]) ^ x)) | |
I hereby claim:
To claim this, I am signing this object:
#include <stdio.h> | |
#include <stdlib.h> | |
int main() { | |
int start = 1573776000; // 15th Nov 2019, 00:00 UTC | |
int end = 1573948800; // // 17th Nov 2019, 00:00 UTC | |
for(int i=start; i<end; i++) { | |
srand(i); | |
int a = rand(); |