Comments (1)
Another option is just to load the file directly in the collab notebook:
import urllib
words = urllib.request.urlopen(
'https://raw.githubusercontent.com/karpathy/makemore/master/names.txt'
).read().decode('utf-8').splitlines()
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Related Issues (20)
- Suggestion: Time Series Forecasting and Transfer Learning
- Factorized code for dC in makemore_part4_backprop.ipynb HOT 1
- zero_grad implementation correctness question HOT 3
- RuntimeError: Trying to backward through the graph a second time (or directly access saved tensors after they have already been freed). Saved intermediate values of the graph are freed when you call .backward() or autograd.grad(). Specify retain_graph=True if you need to backward through the graph a second time or if you need to access saved tensors after calling backward. HOT 1
- Discrepancy in makemore_part1_bigrams single sample draw HOT 2
- Error in makemore_part1_bigrams.ipynb HOT 1
- Missing L.backward() before constructing graph HOT 1
- TypeError: unsupported operand type(s) for +: 'int' and 'Value' HOT 1
- need Discussions :)
- BatchNorm1d in makemore part3 may have error
- makemore_part4_backprop dhpreact exact part is False. HOT 2
- Fun solution to loop replacement (`makemore_part4_backprop.ipynb`)
- name.txt is missing HOT 1
- Problem with makemore_part2_mlp.ipynb HOT 1
- Bug on `lectures/micrograd/micrograd_lecture_second_half_roughly.ipynb` HOT 1
- Neural Network
- Question on Simple Optimization Step HOT 2
- a new way of backprob of C[Xb] instead of for loop HOT 1
- makemore/lecture4/backprop/dC HOT 1
- No keepdim in dbnmeani calculation in makemore_part4_backprop.ipynb
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