Commit Graph

33 Commits

Author SHA1 Message Date
mrq
d29ba75dd6 cleaned up element order with Blocks, also added preset updating the samples/iterations counts 2023-02-05 03:53:46 +00:00
mrq
5c876b81f3 Added small optimization with caching latents, dropped Anaconda for just a py3.9 + pip + venv setup, added helper install scripts for such, cleaned up app.py, added flag '--low-vram' to disable minor optimizations 2023-02-04 01:50:57 +00:00
mrq
43f45274dd Cleaned up the good-morning-sirs-dialect labels, fixed seed=0 not being a random seed, show seed on output 2023-02-03 01:25:03 +00:00
mrq
74f447e5d0 QoL fixes 2023-02-02 21:13:28 +00:00
James Betker
5dc3e269b3
Merge pull request #233 from kianmeng/fix-typos
Fix typos
2023-01-17 18:24:24 -07:00
chris
7ce3dc7bf1 add explicit requirements.txt usage for dep installation 2023-01-11 10:50:18 -05:00
원빈 정
b3d67dcc6b Add reference of univnet implementation 2023-01-06 15:57:02 +09:00
Kian-Meng Ang
551fe655ff Fix typos
Found via `codespell -S *.json -L splitted,nd,ser,broadcat`
2023-01-06 11:04:36 +08:00
James Betker
f28a116b48
Update README.md 2022-12-05 13:16:36 -08:00
Harry Coultas Blum
2efc5a3e50 Added keyword argument 2022-07-08 14:28:24 +01:00
James Betker
00f8bc5e78
Update README.md 2022-06-23 15:57:50 -07:00
Jai Mu
5bff5dd819
Update README.md
Useless update but it was bothering me.
2022-05-22 00:56:06 +09:30
James Betker
5d5aacc38c v2.4 2022-05-17 12:15:13 -06:00
James Betker
8c0b3855bf Release notes for 2.3 2022-05-12 20:26:24 -06:00
James Betker
099bf8363c Update README with suggestions for windows installation 2022-05-08 20:44:44 -06:00
James Betker
ffd0238a16 v2.2 2022-05-06 00:11:10 -06:00
James Betker
b327be56c6 Update readme with prompt engineering 2022-05-03 21:32:06 -06:00
James Betker
e93e5a0c16 Add setup 2022-05-02 21:24:34 -06:00
James Betker
98afa484f1 Update README and update to version 2.1 2022-05-02 21:02:29 -06:00
James Betker
a4cda68ddf getting ready for 2.1 release 2022-05-02 20:20:50 -06:00
James Betker
0ffc191408 Add support for extracting and feeding conditioning latents directly into the model
- Adds a new script and API endpoints for doing this
- Reworks autoregressive and diffusion models so that the conditioning is computed separately (which will actually provide a mild performance boost)
- Updates README

This is untested. Need to do the following manual tests (and someday write unit tests for this behemoth before
it becomes a problem..)
1) Does get_conditioning_latents.py work?
2) Can I feed those latents back into the model by creating a new voice?
3) Can I still mix and match voices (both with conditioning latents and normal voices) with read.py?
2022-05-01 17:25:18 -06:00
James Betker
e857911fca ack 2022-04-27 23:22:55 -06:00
James Betker
524ae1a5a8 tortoise-detect docs 2022-04-26 10:37:44 -06:00
James Betker
26611b158e updates 2022-04-25 21:28:18 -06:00
James Betker
cbc7ba0a63 update readme 2022-04-25 21:19:02 -06:00
James Betker
2a5166d9e1 add regenerate option 2022-04-25 20:05:21 -06:00
James Betker
073b27ccbe update 2022-04-25 17:02:59 -06:00
James Betker
a064290559 Update documentation, add optional verbosity 2022-04-25 16:59:04 -06:00
James Betker
31f7372024 Another update 2022-03-10 23:33:48 -07:00
James Betker
048b0996bc Update readme 2022-03-10 23:32:35 -07:00
James Betker
1a2fb5db63 Update docs 2022-02-03 22:18:21 -07:00
James Betker
5a958b4f4b Initial commit 2022-01-27 23:19:29 -07:00
James Betker
051f500010
Initial commit 2022-01-27 21:33:15 -07:00