CODELABS . DEVELOPERS . GOOGLE . COM {}

Detected CMS Systems:

Blogger (1 occurrences)

Analyzed Page
Matching Content Categories
CMS
Monthly Traffic Estimate
How Does Codelabs.developers.google.com Make Money
Keywords
Topics
Questions
Social Networks
External Links
Libraries

We are analyzing https://codelabs.developers.google.com/codelabs/responsible-ai/agile-classifiers.

Title:
Showcasing Agile Safety Classifiers with Gemma | Google Codelabs
Description:
No description found...
Website Age:
27 years and 9 months (reg. 1997-09-15).

Matching Content Categories {📚}

Games
Photography
Education

Content Management System {📝}

What CMS is codelabs.developers.google.com built with?

Codelabs.developers.google.com operates using BLOGGER.

Traffic Estimate {📈}

What is the average monthly size of codelabs.developers.google.com audience?

🌟 Strong Traffic: 100k - 200k visitors per month

Based on our best estimate, this website will receive around 100,019 visitors per month in the current month.
However, some sources were not loaded, we suggest to reload the page to get complete results.

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How Does Codelabs.developers.google.com Make Money? {💸}

We're unsure how the site profits.

Some websites aren't about earning revenue; they're built to connect communities or raise awareness. There are numerous motivations behind creating websites. This might be one of them. Codelabs.developers.google.com might be plotting its profit, but the way they're doing it isn't detectable yet.

Keywords {🔍}

model, text, str, import, dataset, separator, prompt, output, negative, google, tokens, classifier, lora, score, keras, positive, codelab, training, def, return, token, console, finetuning, prediction, classes, agile, gemma, train, examples, colab, ethos, speech, time, tensorflow, test, classification, classify, nice, today, function, labels, probabilities, scores, aucroc, developer, safety, pet, makes, data, performance,

Topics {✒️}

youtube detect hate speech load ethos dataset detecting hateful speech ethos dataset paper ethos nice today classification fine-tuning technique agile text classifiers store fine-tuning process f'auc-roc pet methods update false positive rate potential prediction errors low-rank adaptation parameter efficient tuning recent version keras json credentials file metrics import confusion_matrix false positive errors training lora weights metrics import f1_score metrics import roccurvedisplay roc-auc score auc-roc scores true positive rate lora pet method prompt = f'{instructions} predicted class score hundred training examples evaluate model predictions fine-tuning token_logits = [vocab_logits[ix] customised text classifier smaller gemma model return [token_probabilities[token] f'f1 horrible language df = df df_test = df[ hand captures safety tasks def preprocess_text prediction errors f'text df['hateful'] = confusion_matrix=cm safety classifier agile classifier

Questions {❓}

Generate('Question: what is the capital of France?

Social Networks {👍}(3)

External Links {🔗}(32)

Libraries {📚}

Video.js

2.66s.