pacman100

# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software

MihailCosmin

#!/bin/bash

### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###

### to verify your gpu is cuda enable check

X-TRON404

#!/bin/bash

### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###

### to verify your gpu is cuda enable check

mht-sharma

import os
import time
from typing import Optional, Tuple

import torch
from PIL import Image

import onnxruntime as onnxrt
import requests
from transformers import AutoConfig, AutoModelForVision2Seq, TrOCRProcessor, VisionEncoderDecoderModel

primus852

#!/bin/bash

### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###

### to verify your gpu is cuda enable check

eldrin

import math
from typing import Callable, Optional
from warnings import warn

import torch
from torch import Tensor
from torchaudio import functional as F
from torchaudio.compliance import kaldi

jlgabriel

import requests
import math
import pandas as pd
import flatten_json  
# instalar flatten_json con: pip install flatten_json 
# Referencia: https://github.com/amirziai/flatten

# parámetros

url_api_productos_contar = "https://api.jumpseller.com/v1/products/count.json"

mauri870

import tensorflow as tf
# FIXME: audio_ops.decode_wav is deprecated, use tensorflow_io.IOTensor.from_audio
from tensorflow.contrib.framework.python.ops import audio_ops

# Enable eager execution for a more interactive frontend.
# If using the default graph mode, you'll probably need to run in a session.
tf.enable_eager_execution()

@tf.function
def audio_to_mfccs(

feroult

import tensorflow as tf

from open_seq2seq.utils.utils import get_base_config, check_logdir, create_model

# Change with your configs here
args_S2T = ["--config_file=/data/training/v5/config-J5x3.py",
        "--mode=interactive_infer",
        "--logdir=/data/training/v5/models",
        "--batch_size_per_gpu=10",
]

zhanwenchen

import os
import tensorflow as tf

trained_checkpoint_prefix = 'checkpoints/dev'
export_dir = os.path.join('models', '0') # IMPORTANT: each model folder must be named '0', '1', ... Otherwise it will fail!

loaded_graph = tf.Graph()
with tf.Session(graph=loaded_graph) as sess:
    # Restore from checkpoint
    loader = tf.train.import_meta_graph(trained_checkpoint_prefix + '.meta')