|
|
467fa1c5ee
|
wrapper fixes
|
2024-04-16 10:19:02 -05:00 |
|
|
|
f0c4baeb25
|
added Adagrad (experimenting with it), added 'extended' model size (16 layers instead of 12, experimenting with it)
|
2024-04-09 22:04:01 -05:00 |
|
|
|
4d75ee066c
|
actually do the Linear replacement with TE's Linear
|
2024-04-09 14:41:13 -05:00 |
|
|
|
9d97eb5104
|
added FP8 support through NVIDIA/TransformerEngine, added RetNet_HF through syncdoth/RetNet (as an alternative to branch away from torchscale)
|
2024-04-08 20:14:51 -05:00 |
|
|
|
f3c59c3e7e
|
cleaner replacement code (because I realized BitNet had an implementation for it too), added calculating gradient norm and performing gradient clipping in local trainer (non-deepspeed)
|
2024-03-01 20:18:43 -06:00 |
|
|
|
47435207f7
|
Added cfg.bitsandbytes.replace as a less intrusive alternative to cfg.bitsandbytes.inject to replace all Linear modules in a model
|
2024-03-01 19:20:10 -06:00 |
|
|
|
35d78a2bb0
|
Yet Another Underlying Transformer Implementation (BitNet, will give it a few days to see how it fares)
|
2024-02-29 20:29:17 -06:00 |
|
|
|
65f500083d
|
tweaks to try and get deepspeed quantized inferencing, validating bitsandbytes and deepspeed quantization, nothing seems to work
|
2023-10-12 22:21:43 -05:00 |
|
|
|
712808494f
|
added support for optional prodigy optimizer (https://github.com/konstmish/prodigy) although it consumes a lot more VRAM per parameter
|
2023-09-06 20:33:16 -05:00 |
|
|
|
100ca6b7d0
|
added option to use SGD optimizer through the YAML, added option to pass in additional optimizer parameters through the YAML, added experimental unified AR+NAR model (does not seem fruitful in testing)
|
2023-09-06 18:58:35 -05:00 |
|
|
|
f6597e2dfe
|
adjustments
|
2023-08-02 18:36:26 -05:00 |
|
|
|
bf8cedc9dd
|
Rewrite init
|
2023-08-02 21:53:35 +00:00 |
|
