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python my_main.py --model mistralai/Mistral-7B-v0.1 --save out --masks_per_iter 100 | |
torch 1.10.1 | |
transformers 4.36.1 | |
accelerate 0.25.0 | |
# of gpus: 1 | |
Namespace(model='mistralai/Mistral-7B-v0.1', seed=0, nsamples=14, sparsity_ratio=0.5, prune_frac=0.1, bsz=14, mlp_attn_ratio=1.0, prune_method='magnitude', cache_dir='llm_weights', use_variant=False, save='out', save_model=None, masks_per_iter=100, tol=0.02, sm_reg_weight='[1e2, 1e-4, 0]', sm_lr_factor='[100, 10, 1, 0.1]', sm_reg_type='l1', sm_lin_model_type='global', sm_bsz='[32, 64, 128]', sm_nepochs=50, wandb_project_name='Prune-No-Backward') | |
wandb: Currently logged in as: skolawol (shapelyprune). Use `wandb login --relogin` to force relogin | |
wandb: Tracking run with wandb version 0.16.1 |
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2023-02-09 11:38:54,186 INFO:Run name: EUR-Lex_bert_20230209113854 | |
2023-02-09 11:38:54,800 INFO:Created a temporary directory at /tmp/tmp5_bwr35i | |
2023-02-09 11:38:54,800 INFO:Writing /tmp/tmp5_bwr35i/_remote_module_non_scriptable.py | |
2023-02-09 11:38:55,241 INFO:Global seed set to 1337 | |
2023-02-09 11:38:55,246 INFO:Using device: cuda | |
2023-02-09 11:38:56,089 INFO:Load data from data/EUR-Lex/train.txt. | |
2023-02-09 11:38:56,930 INFO:Load data from data/EUR-Lex/test.txt. | |
2023-02-09 11:38:57,126 INFO:Finish loading dataset (train: 12359 / val: 3090 / test: 3865) | |
2023-02-09 11:38:57,128 INFO:Initialize model from scratch. | |
2023-02-09 11:38:57,136 INFO:Read 3956 labels. |
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Traceback (most recent call last): | |
File "/usr/lib/python3.7/urllib/request.py", line 1350, in do_open | |
encode_chunked=req.has_header('Transfer-encoding')) | |
File "/usr/lib/python3.7/http/client.py", line 1281, in request | |
self._send_request(method, url, body, headers, encode_chunked) | |
File "/usr/lib/python3.7/http/client.py", line 1327, in _send_request | |
self.endheaders(body, encode_chunked=encode_chunked) | |
File "/usr/lib/python3.7/http/client.py", line 1276, in endheaders | |
self._send_output(message_body, encode_chunked=encode_chunked) | |
File "/usr/lib/python3.7/http/client.py", line 1036, in _send_output |
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name: Build Docker image and deploy to Heroku | |
on: | |
# Trigger the workflow on push or pull request, | |
# but only for the main branch | |
push: | |
branches: | |
- main | |
jobs: | |
build: |
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# Grab the Python slim image | |
FROM python:3.8-slim | |
# Install python and pip | |
COPY requirements.txt ./requirements.txt | |
# Install dependencies | |
RUN pip install --no-cache-dir -r requirements.txt | |
# Add our code |
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# Grab the Python base image | |
FROM python:3.8 | |
# Install python and pip | |
COPY requirements.txt ./requirements.txt | |
# Install dependencies | |
RUN pip install -r requirements.txt | |
# Add our code |
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import numpy as np | |
import plotly.express as px | |
import streamlit as st | |
st.title('Distribution Tester') | |
st.write('Pick a distribution from the list and we shall draw \ | |
the line chart from a random sample from the distribution') | |
keys = ['Normal','Uniform'] | |
dist_key = st.selectbox('Which distribution do you want to plot?', keys) |
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import pyttsx3 | |
engine = pyttsx3.init() | |
engine.say("My guy!") | |
engine.runAndWait() |