ekellbuch

Chillee

import torch
from torch.nn.attention._flex_attention import _create_block_mask, _create_mask
from functools import partial
from torch.nn.attention._flex_attention import _flex_attention
from triton.testing import do_bench
import torch.nn.functional as F
from functools import lru_cache
torch.set_default_device('cuda')

# Example usage

lucataco

""" To use: install Ollama, clone OpenVoice, run this script in the OpenVoice directory
    brew install portaudio
    brew install git-lfs
    git lfs install

    git clone https://github.com/myshell-ai/OpenVoice
    cd OpenVoice
    git clone https://huggingface.co/myshell-ai/OpenVoice
    cp -r OpenVoice/* .
    

thomwolf

""" To use: install LLM studio (or Ollama), clone OpenVoice, run this script in the OpenVoice directory
    git clone https://github.com/myshell-ai/OpenVoice
    cd OpenVoice
    git clone https://huggingface.co/myshell-ai/OpenVoice
    cp -r OpenVoice/* .
    pip install whisper pynput pyaudio
"""

from openai import OpenAI
import time

buttercutter

# [Mamba: Linear-Time Sequence Modeling with Selective State Spaces](https://arxiv.org/abs/2312.00752)

import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import DataLoader, Dataset
from torch.nn import functional as F
from einops import rearrange, repeat
from tqdm import tqdm

Maximilian-Winter

import inspect
import json
import re
import typing
from inspect import isclass, getdoc
from types import NoneType

from pydantic import BaseModel, Field
from pydantic.fields import FieldInfo
from typing import Any, Type, List, get_args, get_origin, Tuple, Union, Optional

veekaybee

Anti-hype LLM reading list

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.

Foundational Concepts

Pre-Transformer Models

tongyx361

"""
GPU Monitor with Email and Execution

This script monitors the usage of GPUs on a system and, when there are enough free GPUs, execute a specified function.
The function run a bash script by default but could be any other executable code.
This script uses the GPUtil library to monitor GPU usage.

Preparation:
    1. `pip install GPUtil`
    2. define your own `func` if needed

CGamesPlay

aarushik93

import weaviate
import csv
import openai

from weaviate.util import generate_uuid5, get_valid_uuid
from uuid import uuid4

OPENAI_API_KEY = "YOUR KEY"
WEAVIATE_URL = "YOUR URL"
openai.api_key = "YOUR KEY"