A "Best of the Best Practices" (BOBP) guide to developing in Python.
- "Build tools for others that you want to be built for you." - Kenneth Reitz
- "Simplicity is alway better than functionality." - Pieter Hintjens
# post_loc.txt contains the json you want to post | |
# -p means to POST it | |
# -H adds an Auth header (could be Basic or Token) | |
# -T sets the Content-Type | |
# -c is concurrent clients | |
# -n is the number of requests to run in the test | |
ab -p post_loc.txt -T application/json -H 'Authorization: Token abcd1234' -c 10 -n 2000 http://example.com/api/v1/locations/ |
Movies Recommendation:
Music Recommendation:
""" | |
Usage: python remove_output.py notebook.ipynb [ > without_output.ipynb ] | |
Modified from remove_output by Minrk | |
""" | |
import sys | |
import io | |
import os | |
from IPython.nbformat.current import read, write |
This worked on 14/May/23. The instructions will probably require updating in the future.
llama is a text prediction model similar to GPT-2, and the version of GPT-3 that has not been fine tuned yet. It is also possible to run fine tuned versions (like alpaca or vicuna with this. I think. Those versions are more focused on answering questions)
Note: I have been told that this does not support multiple GPUs. It can only use a single GPU.
It is possible to run LLama 13B with a 6GB graphics card now! (e.g. a RTX 2060). Thanks to the amazing work involved in llama.cpp. The latest change is CUDA/cuBLAS which allows you pick an arbitrary number of the transformer layers to be run on the GPU. This is perfect for low VRAM.
08737ef720f0510c7ec2aa84d7f70c691073c35d
.Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts and experience preferred (super rare at this point).