aliasgerovs commited on
Commit
2ef7756
1 Parent(s): d0b56d8
Files changed (2) hide show
  1. nohup.out +38 -0
  2. predictors.py +5 -5
nohup.out CHANGED
@@ -23,3 +23,41 @@ Traceback (most recent call last):
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  File "/usr/local/lib/python3.9/dist-packages/transformers/modeling_utils.py", line 2182, in from_pretrained
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  raise EnvironmentError(
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  OSError: polygraf-ai/quillbot-detector-roberta-base-28K does not appear to have a file named pytorch_model.bin, tf_model.h5, model.ckpt or flax_model.msgpack.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  File "/usr/local/lib/python3.9/dist-packages/transformers/modeling_utils.py", line 2182, in from_pretrained
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  raise EnvironmentError(
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  OSError: polygraf-ai/quillbot-detector-roberta-base-28K does not appear to have a file named pytorch_model.bin, tf_model.h5, model.ckpt or flax_model.msgpack.
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+ 2024-03-27 11:14:47.090743: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
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+ 2024-03-27 11:14:47.090847: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
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+ 2024-03-27 11:14:47.092787: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
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+ 2024-03-27 11:14:47.101435: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
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+ To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
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+ 2024-03-27 11:14:48.367455: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
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+ [nltk_data] Downloading package punkt to /root/nltk_data...
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+ [nltk_data] Package punkt is already up-to-date!
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+ [nltk_data] Downloading package punkt to /root/nltk_data...
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+ [nltk_data] Package punkt is already up-to-date!
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+ [nltk_data] Downloading package stopwords to /root/nltk_data...
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+ [nltk_data] Package stopwords is already up-to-date!
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+ [nltk_data] Downloading package punkt to /root/nltk_data...
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+ [nltk_data] Package punkt is already up-to-date!
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+ [nltk_data] Downloading package punkt to /root/nltk_data...
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+ [nltk_data] Package punkt is already up-to-date!
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+ [nltk_data] Downloading package stopwords to /root/nltk_data...
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+ [nltk_data] Package stopwords is already up-to-date!
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+ error: externally-managed-environment
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+
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+ × This environment is externally managed
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+ ╰─> To install Python packages system-wide, try apt install
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+ python3-xyz, where xyz is the package you are trying to
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+ install.
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+
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+ If you wish to install a non-Debian-packaged Python package,
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+ create a virtual environment using python3 -m venv path/to/venv.
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+ Then use path/to/venv/bin/python and path/to/venv/bin/pip. Make
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+ sure you have python3-full installed.
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+
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+ If you wish to install a non-Debian packaged Python application,
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+ it may be easiest to use pipx install xyz, which will manage a
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+ virtual environment for you. Make sure you have pipx installed.
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+
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+ See /usr/share/doc/python3.11/README.venv for more information.
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+
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+ note: If you believe this is a mistake, please contact your Python installation or OS distribution provider. You can override this, at the risk of breaking your Python installation or OS, by passing --break-system-packages.
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+ hint: See PEP 668 for the detailed specification.
predictors.py CHANGED
@@ -276,11 +276,11 @@ def predict_bc_scores(input):
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  average_bc_scores = np.mean(bc_scores_array, axis=0)
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  bc_score_list = average_bc_scores.tolist()
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  print(f"Original BC scores: AI: {bc_score_list[1]}, HUMAN: {bc_score_list[0]}")
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- # isotonic regression calibration
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- ai_score = iso_reg.predict([bc_score_list[1]])[0]
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- human_score = 1 - ai_score
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- bc_score = {"AI": ai_score, "HUMAN": human_score}
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- print(f"Calibration BC scores: AI: {ai_score}, HUMAN: {human_score}")
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  return bc_score
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  average_bc_scores = np.mean(bc_scores_array, axis=0)
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  bc_score_list = average_bc_scores.tolist()
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  print(f"Original BC scores: AI: {bc_score_list[1]}, HUMAN: {bc_score_list[0]}")
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+ # # isotonic regression calibration
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+ # ai_score = iso_reg.predict([bc_score_list[1]])[0]
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+ # human_score = 1 - ai_score
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+ bc_score = {"AI": bc_score_list[1], "HUMAN": bc_score_list[0]}
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+ # print(f"Calibration BC scores: AI: {ai_score}, HUMAN: {human_score}")
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  return bc_score
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