Also dynamically limit the GPU layers and context length fields to the maximum supported by the model.
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
- Use F16 KV cache
- Store transposed V in the cache
- Avoid unnecessary Q copy
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
ggml upstream commit 0265f0813492602fec0e1159fe61de1bf0ccaf78
* backend/gptj: use scratch buffers
reduces total memory required and makes eval buf not grow with n_past
* backend/mpt: use scratch bufs
* fix format-related compile warnings
* backend: factor out common structs in model code
prepping to hack on these by hopefully making there be fewer places to fix the same bug
rename
* use common buffer wrapper instead of manual malloc
* fix replit compile warnings
most of these can just shortcut out of the model loading logic llama is a bit worse to deal with because we submodule it so I have to at least parse the hparams, and then I just use the size on disk as an estimate for the mem size (which seems reasonable since we mmap() the llama files anyway)
fixes a definite use-after-free and likely avoids some other
potential ones - std::string will convert to a std::string_view
automatically but as soon as the std::string in question goes out of
scope it is already freed and the string_view is pointing at freed
memory - this is *mostly* fine if its returning a reference to the
tokenizer's internal vocab table but it's, imo, too easy to return a
reference to a dynamically constructed string with this as replit is
doing (and unfortunately needs to do to convert the internal whitespace
replacement symbol back to a space)
Major change to the backend that allows for pluggable versions of llama.cpp/ggml. This was squashed merged from dlopen_backend_5 where the history is preserved.
Improves output quality by making these tokenizers more closely
match the behavior of the huggingface `tokenizers` based BPE
tokenizers these models were trained with.
Featuring:
* Fixed unicode handling (via ICU)
* Fixed BPE token merge handling
* Complete added vocabulary handling
Caught with AddressSanitizer running a basic prompt test against llmodel
standalone. This fix allows ASan builds to complete a simple prompt
without illegal accesses but there are still notably several leaks.
