Monitor and guard against harmful content in language models

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  • License: MIT License
  • Author: Wisent Team
  • Tags nlp , machine learning , language models , safety , guardrails , lm-evaluation-harness
  • Requires: Python >=3.8
  • Provides-Extra: harness , cuda
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Project description

Wisent Banner

pip install wisent

Overview

Wisent allows you to control your AI by identifying brain patterns corresponding to responses you don't like, like hallucinations or harmful outputs. We use contrastive pairs of representations to detect when a model might be generating harmful content or hallucinating. Learn more at wisent.ai/documentation.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for lbartoszcze from gravatar.com lbartoszcze

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License
  • Author: Wisent Team
  • Tags nlp , machine learning , language models , safety , guardrails , lm-evaluation-harness
  • Requires: Python >=3.8
  • Provides-Extra: harness , cuda
Classifiers

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0.7.78

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0.7.75

0.7.74

0.7.73

0.7.72

0.7.71

0.7.70

0.7.69

0.7.68

0.7.67

0.7.66

0.7.65

0.7.64

0.7.63

0.7.62

0.7.61

0.7.60

0.7.59

0.7.58

0.7.57

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0.7.55

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0.7.51

0.7.50

0.7.49

0.7.48

0.7.47

0.7.46

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0.7.43

0.7.42

0.7.41

0.7.40

0.7.39

0.7.38

0.7.37

0.7.36

0.7.35

0.7.34

0.7.33

0.7.32

0.7.31

0.7.30

0.7.29

0.7.28

0.7.27

0.7.26

0.7.25

0.7.23

0.7.22

0.7.21

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0.7.15

0.7.13

0.7.12

0.7.11

0.7.10

0.7.9

0.7.8

0.7.7

0.7.6

0.7.5

0.7.4

0.7.3

0.7.2

0.7.1

This version

0.6.6

0.6.5

0.6.4

0.6.3

0.6.2

0.6.1

0.5.85

0.5.84

0.5.83

0.5.82

0.5.81

0.5.80

0.5.79

0.5.78

0.5.77

0.5.76

0.5.75

0.5.74

0.5.73

0.5.72

0.5.69

0.5.68

0.5.67

0.5.65

0.5.64

0.5.63

0.5.62

0.5.61

0.5.60

0.5.59

0.5.58

0.5.57

0.5.56

0.5.55

0.5.54

0.5.53

0.5.52

0.5.51

0.5.50

0.5.49

0.5.48

0.5.47

0.5.46

0.5.45

0.5.44

0.5.43

0.5.42

0.5.41

0.5.40

0.5.39

0.5.38

0.5.37

0.5.36

0.5.35

0.5.34

0.5.33

0.5.32

0.5.31

0.5.30

0.5.29

0.5.28

0.5.27

0.5.26

0.5.25

0.5.24

0.5.23

0.5.22

0.5.21

0.5.20

0.5.19

0.5.18

0.5.17

0.5.16

0.5.15

0.5.14

0.5.13

0.5.12

0.5.11

0.5.10

0.5.9

0.5.8

0.5.7

0.5.6

0.5.5

0.5.4

0.5.3

0.5.2

0.5.1

0.1.1

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