main-database/JASCO.yaml at preview · Language-Technology-Assessment/main-database · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
---
# Thank you for contributing!
# In filling out this yaml file, please follow the criteria as described here:
# https://osai-index.eu/contribute

# You're free to build on this work and reuse the data. It is licensed under CC-BY 4.0, with the
# stipulation that attribution should come in the form of a link to https://osai-index.eu/
# and a citation to the peer-reviewed paper in which the dataset & criteria were published:

# Liesenfeld, A. and Dingemanse, M., 2024. Rethinking open source generative AI: open-washing and the EU AI Act. In Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency (pp. 1774-1787).

# Organization tags:
# - National origin: United States
# - Contributor type: Non-academic (American Big Tech)

system:
    name: JASCO
    link: https://huggingface.co/facebook/jasco-chords-drums-melody-1B
    type: audio
    performanceclass: limited
    basemodelname:
    endmodelname: JASCO-Chords-Drums-Melody-1B
    endmodellicense: CC-BY-NC-4.0
    releasedate: 2025-01
    notes: Conditional audio generation based on audio samples or text.

org:
    name: Meta
    link: https://ai.meta.com/
    notes: Meta, a major technology company.

# availability:
datasources_basemodel:
    class: closed
    link:
    notes:

datasources_endmodel:
    class: closed
    link:
    notes:

weights_basemodel:
    class: open
    link: https://huggingface.co/facebook/jasco-chords-drums-melody-1B
    notes:

weights_endmodel:
    class: open
    link: https://huggingface.co/facebook/jasco-chords-drums-melody-1B
    notes:

trainingcode:
    class: open
    link: https://github.com/facebookresearch/audiocraft
    notes: Training code provided through GitHub.

# documentation:
code:
    class: open
    link: https://github.com/facebookresearch/audiocraft
    notes: Repository thoroughly documented.

hardware_architecture:
    class: closed
    link:
    notes:

preprint:
    class: open
    link: https://arxiv.org/abs/2406.10970
    notes:

paper:
    class: closed
    link:
    notes:

modelcard:
    class: open
    link: https://huggingface.co/papers/2406.10970
    notes:

datasheet:
    class: closed
    link:
    notes:

# access:
package:
    class: closed
    link:
    notes:

api:
    class: closed
    link:
    notes:
    metaprompts:

licenses:
    class: partial
    link:
    notes: "weights as CC-BY-NC-4.0"