ee682702ee
Merge branch 'KoboldAI:main' into united
2022-04-05 01:35:22 +02:00
8153f21d5c
Convo 6B
2022-04-05 01:33:51 +02:00
04707abde6
Merge pull request #109 from VE-FORBRYDERNE/requirements
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Remove Ray from requirements_mtj.txt
2022-04-04 19:17:56 +02:00
66bc7e10bf
Remove Ray from requirements_mtj.txt
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I made some changes recently to mesh transformer JAX so that we don't
need Ray anymore. This should make the installation a little faster.
2022-04-04 12:42:33 -04:00
0882ba165c
Merge pull request #108 from VE-FORBRYDERNE/lazy-loader
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Lazy loader Python 3.6 compatibility
2022-04-03 01:15:48 +02:00
fabbdf2bb1
Lazy loader Python 3.6 compatibility
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The current lazy loader relies on a feature of the Python zipfile module
that was added in Python 3.7.0:
https://bugs.python.org/issue22908
This commit adds compatibility for Python 3.6.
2022-04-02 15:02:54 -04:00
d9670f4e16
Revert "add colab cell to start ECILA"
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This reverts commit 231418e15e
2022-03-29 07:23:36 +02:00
231418e15e
add colab cell to start ECILA
2022-03-29 07:21:23 +02:00
8368b20421
Merge pull request #107 from VE-FORBRYDERNE/typical
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Typical sampling needs to use nansum instead of sum
2022-03-28 11:13:38 +02:00
67e28d2b5c
Typical sampling needs to use nansum instead of sum
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If `probs` is zero then `log_probs` will be negative infinity, and the
calculation of `neg_entropy` would then give NaN because zero times
infinity is a mathematically indeterminate value.
We need to use nansum so that those NaN values are treated as zeros to
ignore them in the entropy calculation.
2022-03-28 00:02:31 -04:00
e644963564
OpenAI Fixes
2022-03-28 02:02:37 +02:00
77ae893f4d
Merge pull request #106 from VE-FORBRYDERNE/typical
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Typical sampling
2022-03-28 00:14:09 +02:00
e2cd49d552
Typo fix in `TypicalLogitsWarper`
2022-03-27 17:08:57 -04:00
bbd0a83fef
Fix `TypicalLogitsWarper` argument typing
2022-03-27 16:59:23 -04:00
d5989d4c62
Hide division by zero warning in JAX typical filter
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This warning happens when `np.log` gets an input containing zeros.
In that case, NumPy will throw a warning and output negative infinity.
Negative infinity is the correct behaviour here, so we can safely ignore
the warning.
2022-03-27 16:57:12 -04:00
20e48b11d7
Typical sampling
2022-03-27 16:25:50 -04:00
aa8de64aa4
fix default port
2022-03-25 23:26:27 +01:00
3e003d3b42
add port to the command options
2022-03-25 22:18:28 +01:00
076c6c8efa
update slider value without waiting for socketio
2022-03-25 22:18:00 +01:00
72b74d9ab6
fix tabs
2022-03-25 20:46:08 +01:00
6aaa8d026f
semicolon
2022-03-25 20:44:41 +01:00
8270d92073
fix wrong this scope
2022-03-25 20:44:25 +01:00
6ed50ee1e9
make the throttle timer a dict to keep track of which slider has been changed
2022-03-25 20:37:45 +01:00
1de4944d46
Add throttle closure for settings sliders
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Adds a throttling closure to add a waiting time before calling a callback,
Uses this closure to throttle the event fired by socketio on slider value change
2022-03-25 20:08:56 +01:00
e4c72ca2e5
Merge pull request #104 from VE-FORBRYDERNE/retry-randomgame
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Allow regenerating random story using Retry button
2022-03-24 12:57:04 +01:00
0348970b19
Make sure AI is not busy when using retry to regenerate random story
2022-03-23 22:09:35 -04:00
4832dd6f37
Allow regenerating random story using Retry button
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Commit b55e5a8e0b
2022-03-23 13:39:46 -04:00
38d78d10db
Merge pull request #103 from VE-FORBRYDERNE/neox
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Divide GPT-NeoX replicated bias layers by 4 again instead of by 8
2022-03-21 02:19:32 +01:00
cf99f02ca5
Merge branch 'main' into united
2022-03-20 19:22:53 +01:00
20eab085dd
Fix AutoSave Toggle
2022-03-20 19:12:11 +01:00
5c795609e4
KML Fix
2022-03-20 13:10:56 +01:00
73aecc0510
Divide NeoX replicated bias layers by 4 again instead of by 8
2022-03-20 01:04:55 -04:00
f1487a4551
New Linux Runtime
2022-03-20 00:00:21 +01:00
a7f652f293
Merge pull request #101 from VE-FORBRYDERNE/neox
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GPT-NeoX-20B support in Colab TPU instances
2022-03-19 09:56:15 +01:00
05fc46b253
Changing this again to divide by 8
2022-03-19 02:09:41 -04:00
b1125a6705
Add EOS and padding token to default NeoX badwords
2022-03-19 01:30:02 -04:00
6c20d0d657
Nevermind, dividing by 4 is actually correct...
2022-03-19 00:55:04 -04:00
f16b61ec77
Should divide NeoX replicated parameters by 8 (not by 4)
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Also, suppresses the PyTorch 1.11 warning about transposing tensors with
ndim != 2 in the new code
2022-03-19 00:48:33 -04:00
c2c139e940
Change default PE type for NeoX to `neox_rotary`
2022-03-19 00:26:04 -04:00
85a4959efa
Merge branch 'united' into neox
2022-03-18 11:19:03 -04:00
f581fe89cb
Torch version changes
2022-03-17 21:11:36 +01:00
9e9c1c3fe0
Merge pull request #100 from VE-FORBRYDERNE/patch
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Add PyTorch 1.11 support for lazy loader
2022-03-17 21:06:38 +01:00
c444260eac
Silence PyTorch warning about transposing tensors with dimension != 2
2022-03-17 15:16:56 -04:00
ef21ab9c91
PyTorch 1.9 lazy loader compatibility bugfix
2022-03-17 14:10:51 -04:00
eaf190469d
Add PyTorch 1.11 support for lazy loader
2022-03-17 12:51:41 -04:00
9235754eb9
Dependency Fixes
2022-03-17 00:35:59 +01:00
a3e5e052b3
Newer umamba + slope tweak
2022-03-16 18:34:02 +01:00
95c4251db9
Print two newlines before loading HF models
2022-03-15 13:58:53 -04:00
9e2848e48f
Show parameter count when loading GPT-NeoX in Colab TPU instance
2022-03-15 13:55:27 -04:00
9dc48b15f0
Add custom badwords and pad token ID for GPT-NeoX
2022-03-14 23:31:49 -04:00
henk717
Gnome Ann
Noli
nolialsea