llama.cpp/gguf-py/gguf
Ondřej Čertík 7ce2c77f88
gguf : add support for I64 and F64 arrays (#6062)
* gguf : add support for I64 and F64 arrays

GGML currently does not support I64 or F64 arrays and they are not often
used in machine learning, however if in the future the need arises, it
would be nice to add them now, so that the types are next to the other
types I8, I16, I32 in the enums, and it also reserves their type number.

Furthermore, with this addition the GGUF format becomes very usable for
most computational applications of NumPy (being compatible with the most
common NumPy dtypes: i8, i16, i32, i64, f32, f64), providing a faster,
and more versatile alternative to the `npz` format, and a simpler
alternative to the `hdf5` format.

The change in this PR seems small, not significantly increasing the
maintenance burden. I tested this from Python using GGUFWriter/Reader
and `gguf-dump`, as well as from C, everything seems to work.

* Fix compiler warnings
2024-03-15 10:46:51 +02:00
..
__init__.py gguf-py: Refactor and allow reading/modifying existing GGUF files (#3981) 2023-11-11 08:04:50 +03:00
constants.py gguf : add support for I64 and F64 arrays (#6062) 2024-03-15 10:46:51 +02:00
gguf_reader.py gguf : add support for I64 and F64 arrays (#6062) 2024-03-15 10:46:51 +02:00
gguf_writer.py gguf : add support for I64 and F64 arrays (#6062) 2024-03-15 10:46:51 +02:00
gguf.py gguf-py: Refactor and allow reading/modifying existing GGUF files (#3981) 2023-11-11 08:04:50 +03:00
py.typed convert : various script cleanups/fixes + merges and special token handling (#2842) 2023-08-30 11:25:50 +03:00
tensor_mapping.py llama : support Mamba Selective State Space Models (#5328) 2024-03-08 17:31:00 -05:00
vocab.py fix(gguf-py): special tokens are no longer skipped when add_<token>_token is set to false (#5487) 2024-02-15 14:14:37 +01:00