llama.cpp/gguf-py/gguf
compilade 5a419926b0
convert-hf : support bfloat16 conversion (#7158)
* convert-hf : support bfloat16 conversion

* gguf-py : flake8 fixes

* convert-hf : add missing space after comma

* convert-hf : get bit-exact same output as ./quantize

The quantization version was missing.

* convert-hf : don't round bf16 NANs

* convert-hf : save some memory with np.int16 intermediate bf16 weights

* convert-hf : more closely match llama.cpp with which weights to keep in f32

* convert-hf : add --outtype auto-f16

A reason for this to exist is for model quantizers who want an initial
GGUF with the most fidelity to the original model while still using
a 16-bit float type instead of 32-bit floats.

* convert-hf : remove a semicolon because flake8 doesn't like it

It's a reflex from when programming in C/C++, I guess.

* convert-hf : support outtype templating in outfile name

* convert-hf : rename --outtype auto-f16 to --outtype auto
2024-05-11 11:06:26 -04:00
..
__init__.py convert-hf : support bfloat16 conversion (#7158) 2024-05-11 11:06:26 -04:00
constants.py convert-hf : support bfloat16 conversion (#7158) 2024-05-11 11:06:26 -04:00
gguf_reader.py convert-hf : save memory with lazy evaluation (#7075) 2024-05-08 18:16:38 -04:00
gguf_writer.py convert-hf : support bfloat16 conversion (#7158) 2024-05-11 11:06:26 -04:00
gguf.py gguf-py: Refactor and allow reading/modifying existing GGUF files (#3981) 2023-11-11 08:04:50 +03:00
lazy.py convert-hf : support bfloat16 conversion (#7158) 2024-05-11 11:06:26 -04:00
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 : add Jina Embeddings architecture (#6826) 2024-05-11 10:46:09 +03:00
vocab.py convert-hf : save memory with lazy evaluation (#7075) 2024-05-08 18:16:38 -04:00