About this
About this
About this
Tyler Renelle lefnire
lefnire
/ releaseTest.md
Last active
September 17, 2020 04:54
— forked from paperspace-ops/releaseTest.md
lefnire
/ releaseTest.md
Created
September 17, 2020 04:54
— forked from paperspace-ops/releaseTest.md
lefnire
/ bert_dist_cluster.py
Last active
September 16, 2022 13:27
BERT embeddings similarity & clustering
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| import math | |
| import torch | |
| from sklearn.cluster import AgglomerativeClustering | |
| from sentence_transformers import SentenceTransformer | |
| def normalize(x): | |
| """ | |
| Need this method for cosine(), because otherwise we're dealing with dot-product on non-normalized data (which isn't cosine). | |
| BERT embeddings typically range [-7 7], so this is needed. |
lefnire
/ generate_example_data.py.out
Created
October 18, 2019 21:33
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| Generating example data... | |
| [0.223 0. 0. 0. 0. 0.196 0. 0. 0. 0. 0.225 0. | |
| 0. 0. 0. 0.17 0. 0. 0. 0. 0.186 0. 0. 0. | |
| 0. ] | |
| [0.223 0. 0. 0. 0. 0.196 0. 0. 0. 0. 0.225 0. | |
| 0. 0. 0. 0.17 0. 0. 0. 0. 0.186 0. 0. 0. | |
| 0. ] | |
| [0.223 0. 0. 0. 0. 0.196 0. 0. 0. 0. 0.225 0. | |
| 0. 0. 0. 0.17 0. 0. 0. 0. 0.186 0. 0. 0. | |
| 0. ] |
lefnire
/ null_cols.py
Created
June 11, 2018 01:06
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| df = pd.read_csv( | |
| data_path('Model_Update_Data_April_2018.txt'), | |
| sep='\t', | |
| true_values=['Y', 'True', 'TRUE'], | |
| false_values=['N', 'False', 'FALSE'], | |
| na_values=['?', 'U', 'Unknown'] | |
| ) | |
| na_cols = df.columns[df.isna().any()] | |
| print(na_cols) | |
| """ |
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| import {Home} from './Home.js'; | |
| import React from 'react'; | |
| class App extends React.Component { | |
| render() { | |
| return ( | |
| <div className="container container-fluid"> | |
| <!-- maybe some menu / header stuff here. Anything that's shared b/w all your pages --> | |
| <Home /> | |
| </div> |
lefnire
/ gist:948c854a2bf891cd4f2c6b31a365c0af
Created
December 5, 2017 04:15
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| baseline_optimizer.optimizer.learning_rate: 0.1127 | |
| net.activation_tanh: 0.0854 | |
| baseline_optimizer.num_steps: 0.0569 | |
| entropy_regularization: 0.0549 | |
| source_kaggle2: 0.0499 | |
| net.depth: 0.0461 | |
| net.l1: 0.0456 | |
| net.width: 0.0428 | |
| discount: 0.0397 | |
| net.dropout: 0.0375 |
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| 2017-10-06 19:57:20.025172: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations. | |
| 2017-10-06 19:57:20.025184: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations. | |
| 2017-10-06 19:57:20.025186: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations. | |
| 2017-10-06 19:57:20.025188: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations. | |
| 2017-10-06 19:57:20.025189: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA ins |
lefnire
/ gist:1b3d9c99a6a417dfb88e08a1478de5c0
Created
August 10, 2017 01:07
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| (tensorflow1) lefnire@lefnire-ubuntu:~/Sites/btc/github/Multidimensional-LSTM-BitCoin-Time-Series$ python run.py | |
| Using TensorFlow backend. | |
| I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcublas.so.8.0 locally | |
| I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CU |
lefnire
/ gist:1521fdd1c8169b8c0853fa25c88a5046
Created
August 10, 2017 00:49
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| backports.weakref==1.0rc1 | |
| bleach==1.5.0 | |
| cycler==0.10.0 | |
| funcsigs==1.0.2 | |
| functools32==3.2.3.post2 | |
| h5py==2.7.0 | |
| html5lib==0.9999999 | |
| Keras==2.0.6 | |
| Markdown==2.6.8 | |
| matplotlib==2.0.2 |
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