OlivierDehaene 85f10ec5c9 feat(fp8): use fbgemm kernels and load fp8 weights directly (#2248) ... * feat(fp8): add support for fbgemm * allow loading fp8 weights directly * update outlines * fix makefile * build fbgemm * avoid circular import and fix dockerfile * add default dtype * refactored weights loader * fix auto conversion * fix quantization config parsing * force new nccl on install * missing get_weights implementation * increase timeout		2024-09-25 05:30:41 +00:00
..
adapters	Enable multiple LoRa adapters (#2010)	2024-09-24 03:55:04 +00:00
layers	feat(fp8): use fbgemm kernels and load fp8 weights directly (#2248)	2024-09-25 05:30:41 +00:00
models	feat(fp8): use fbgemm kernels and load fp8 weights directly (#2248)	2024-09-25 05:30:41 +00:00
pb	chore: add pre-commit (#1569)	2024-04-24 15:32:02 +03:00
utils	feat(fp8): use fbgemm kernels and load fp8 weights directly (#2248)	2024-09-25 05:30:41 +00:00
__init__.py	feat(clients): Python client (#103)	2023-03-07 18:52:22 +01:00
cache.py	fix(server): decrease memory fragmentation (#557)	2023-07-06 14:28:33 +02:00
cli.py	feat(fp8): use fbgemm kernels and load fp8 weights directly (#2248)	2024-09-25 05:30:41 +00:00
interceptor.py	Aligin the source code with main branch 2.0.4	2024-09-24 03:06:55 +00:00
server.py	Enable multiple LoRa adapters (#2010)	2024-09-24 03:55:04 +00:00
tracing.py	Add OTLP Service Name Environment Variable (#2076)	2024-09-24 03:51:26 +00:00