Models | Examples |
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index index.php index.html; | |
root /your/path/to/the/sendy; | |
location = / { | |
index index.php; | |
} | |
location / { | |
if (!-f $request_filename){ | |
rewrite ^/([a-zA-Z0-9-]+)$ /$1.php last; |
Last week I added an Nvidia Quadro P620 to my QNAP TVS-872XT NAS. For the last few days, I've been trying to get both Plex and Emby docker containers to actually use the Nvidia card for encoding and decoding media streams.
The instructions included in the linuxserver/plex DockerHub container indicate that to use Nvidia hardware decoding, you must first install the docker-nvidia2 runtime from Nvidia. Since QNap
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# Specify a custom format to anonymize your logs | |
$template anonymize,"%$year%-%$month%-%$day% %timegenerated:12:19:date-rfc3339% %app-name% %$!new%\n" | |
# This makes the anonymize template the default for all file actions | |
$ActionFileDefaultTemplate anonymize | |
set $!new = $msg; | |
# Replace credit cards | |
if re_match($msg,'([0-9]{13,16})') |
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from transformers import AutoModelForCausalLM, AutoTokenizer | |
from peft import PeftModel | |
import torch | |
import os | |
import argparse | |
def get_args(): | |
parser = argparse.ArgumentParser() | |
parser.add_argument("--base_model_name_or_path", type=str) |
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""" | |
The code below combines approaches published by both @eugene-yh and @jinyongyoo on Github. | |
Thanks for the contributions guys! | |
""" | |
import torch | |
import peft |
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# Machine Intelligence Made to Impersonate Characteristics: MIMIC | |
# NOTE run this $ conda install -c conda-forge mpi4py mpich to get mpi working | |
# accelerate launch --use_deepspeed -m axolotl.cli.train ./config_name_here | |
base_model: alpindale/Mistral-7B-v0.2-hf | |
base_model_config: alpindale/Mistral-7B-v0.2-hf | |
model_type: MistralForCausalLM | |
tokenizer_type: LlamaTokenizer | |
is_mistral_derived_model: true |