# These are supported funding model platforms

github: [jinzhu]
patreon: jinzhu

/** File generated by Grunt -- do not modify
 *  JQUERY-FORM-VALIDATOR
 *
 *  @version 2.3.77
 *  @website http://formvalidator.net/
 *  @author Victor Jonsson, http://victorjonsson.se
 *  @license MIT
 */

		return
	}

	sizeStr := r.Form.Get(peerRESTSize)
	durationStr := r.Form.Get(peerRESTDuration)
	concurrentStr := r.Form.Get(peerRESTConcurrent)
	storageClass := r.Form.Get(peerRESTStorageClass)
	bucketName := r.Form.Get(peerRESTBucket)
	enableSha256 := r.Form.Get(peerRESTEnableSha256) == "true"
	enableMultipart := r.Form.Get(peerRESTEnableMultipart) == "true"

come with the compiler are not designed to be used with untrusted data and
should be used with caution when working with untrusted models.

### Saved graphs and checkpoints

When loading untrusted serialized computation graphs (in form of a `GraphDef`,
`SavedModel`, or equivalent on-disk format), the set of computation primitives
available to TensorFlow is powerful enough that you should assume that the
TensorFlow process effectively executes arbitrary code.

					<div class="input-group mb-3">
						<c:set var="ph_new_password">
							<la:message key="labels.login.placeholder_new_password" />
						</c:set>
						<la:password property="password" class="form-control"
							placeholder="${ph_new_password}" />
						<div class="input-group-append">
							<span class="input-group-text">
								<em class="fa fa-lock fa-fw">
							</span>
						</div>
					</div>

                                    </la:info>
                                    <la:errors/>
                                </div>
                                <div class="form-group row">
                                    <label class="col-sm-12 col-form-label"><la:message
                                            key="labels.elevate_word_file"/></label>
                                </div>
                            </div>

					<div class="input-group mb-3">
						<c:set var="ph_username">
							<la:message key="labels.login.placeholder_username" />
						</c:set>
						<la:text property="username" styleId="username"
							class="form-control" placeholder="${ph_username}" />
						<div class="input-group-append">
							<span class="input-group-text">
								<em class="fa fa-user fa-fw">
            				</span>
						</div>
					</div>

/** File generated by Grunt -- do not modify
 *  JQUERY-FORM-VALIDATOR
 *
 *  @version 2.3.77
 *  @website http://formvalidator.net/
 *  @author Victor Jonsson, http://victorjonsson.se
 *  @license MIT
 */

 * EncodingHelper provides utility methods for managing and normalizing character encodings.
 * It allows setting a default encoding, mapping various encoding names to preferred ones,
 * and normalizing an encoding string to its preferred form or the default if no mapping is found.
 */
public class EncodingHelper {

    /** The default encoding to use when no mapping is found */
    protected String defaultEncoding;

Stellen wir uns vor, Sie verfügen über einige **Modelle für maschinelles Lernen**, die Sie zur Bearbeitung von Requests verwenden möchten. 🤖

Die gleichen Modelle werden von den Requests gemeinsam genutzt, es handelt sich also nicht um ein Modell pro Request, pro Benutzer, oder ähnliches.