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b3181 #170

Merged
merged 8 commits into from
Jun 18, 2024
Merged

b3181 #170

merged 8 commits into from
Jun 18, 2024

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Nexesenex
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ggerganov and others added 8 commits June 18, 2024 09:50
* whisper : use ggml_backend_sched (wip)

* use sched in whisper_allocr

* whisper : single backend in whisper_context

* whisper : remove whisper_state->backends_used

* whisper : remove whisper_context->backend

* whisper : reset scheduler after init

* whisper : fix external encoder (e.g. CoreML)

* whisper : cleanup

* whisper : handle null GPU buffer types + fix sycl

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Co-authored-by: slaren <[email protected]>
On hosts which are not prepared/dedicated to execute code using CUDA
it is still possible to compile llama.cpp with CUDA support by just
installing the development packages.  Missing are the runtime
libraries like /usr/lib64/libcuda.so* and currently the link step
will fail.

The development environment is prepared for such situations.  There
are stub libraries for all the CUDA libraries available in the
$(CUDA_PATH)/lib64/stubs directory.  Adding this directory to the end
of the search path will not change anything for environments which
currently work fine but will enable compiling llama.cpp also in case
the runtime code is not available.
* Only use FIM middle if it exists

* Only use FIM middle if it exists
* Random test: add_bos_token, add_eos_token
* Random test: add BPE models for testing
* Custom regex split fails with codepoint 0
* Fix falcon punctuation regex
* Refactor llm_tokenizer_bpe: move code to constructor
* Move 'add_special_bos/eos' logic to llm_tokenizer_bpe
* Move tokenizer flags to vocab structure.
* Default values for special_add_bos/eos
* Build vocab.special_tokens_cache using vocab token types
* Generalize 'jina-v2' per token attributes
* Fix unicode whitespaces (deepseek-coder, deepseek-llm)
* Skip missing byte tokens (falcon)
* Better unicode data generation
* Replace char32_t with uint32_t
@Nexesenex Nexesenex merged commit 0136b3f into Nexesenex:skystream Jun 18, 2024
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8 participants