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 of models in prod eagerly sought.
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# | |
# this is adapted from https://github.com/facebookresearch/llama/blob/main/llama/generation.py#L213 | |
# the tokenizer is replaced with ord() to make it easier to see whats actually happening | |
from typing_extensions import TypedDict, Literal | |
from typing import List, Optional | |
Role = Literal["system", "user", "assistant"] | |
class Message(TypedDict): |
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import baker | |
import json | |
import os | |
from cytoolz import merge, join, groupby | |
from cytoolz.compatibility import iteritems | |
from cytoolz.curried import update_in | |
from itertools import starmap | |
from collections import deque | |
from lxml import etree, objectify | |
from scipy.io import savemat |
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""" | |
this code is not mine! i shamelessly copied it from http://stackoverflow.com/questions/19790188/expanding-english-language-contractions-in-python | |
all credits go to alko and arturomp @ stack overflow. | |
basically, it's a big find/replace. | |
""" | |
import re | |
cList = { | |
"ain't": "am not", |
As configured in my dotfiles.
start new:
tmux
start new with session name: