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	6381d4e110
	
	
	
		
			
			* gguf : first API pass
* gguf : read header + meta data
* gguf : read tensor info
* gguf : initial model loading - not tested
* gguf : add gguf_get_tensor_name()
* gguf : do not support passing existing ggml_context to gguf_init
* gguf : simplify gguf_get_val
* gguf : gguf.c is now part of ggml.c
* gguf : read / write sample models
* gguf : add comments
* refactor : reduce code duplication and better API (#2415)
* gguf : expose the gguf_type enum through the API for now
* gguf : add array support
* gguf.py : some code style changes
* convert.py : start a new simplified implementation by removing old stuff
* convert.py : remove GGML vocab + other obsolete stuff
* GGUF : write tensor (#2426)
* WIP: Write tensor
* GGUF : Support writing tensors in Python
* refactor : rm unused import and upd todos
* fix : fix errors upd writing example
* rm example.gguf
* gitignore *.gguf
* undo formatting
* gguf : add gguf_find_key (#2438)
* gguf.cpp : find key example
* ggml.h : add gguf_find_key
* ggml.c : add gguf_find_key
* gguf : fix writing tensors
* gguf : do not hardcode tensor names to read
* gguf : write sample tensors to read
* gguf : add tokenization constants
* quick and dirty conversion example
* gguf : fix writing gguf arrays
* gguf : write tensors one by one and code reuse
* gguf : fix writing gguf arrays
* gguf : write tensors one by one
* gguf : write tensors one by one
* gguf : write tokenizer data
* gguf : upd gguf conversion script
* Update convert-llama-h5-to-gguf.py
* gguf : handle already encoded string
* ggml.h : get array str and f32
* ggml.c : get arr str and f32
* gguf.py : support any type
* Update convert-llama-h5-to-gguf.py
* gguf : fix set is not subscriptable
* gguf : update convert-llama-h5-to-gguf.py
* constants.py : add layer norm eps
* gguf.py : add layer norm eps and merges
* ggml.h : increase GGML_MAX_NAME to 64
* ggml.c : add gguf_get_arr_n
* Update convert-llama-h5-to-gguf.py
* add gptneox gguf example
* Makefile : add gptneox gguf example
* Update convert-llama-h5-to-gguf.py
* add gptneox gguf example
* Update convert-llama-h5-to-gguf.py
* Update convert-gptneox-h5-to-gguf.py
* Update convert-gptneox-h5-to-gguf.py
* Update convert-llama-h5-to-gguf.py
* gguf : support custom alignment value
* gguf : fix typo in function call
* gguf : mmap tensor data example
* fix : update convert-llama-h5-to-gguf.py
* Update convert-llama-h5-to-gguf.py
* convert-gptneox-h5-to-gguf.py : Special tokens
* gptneox-main.cpp : special tokens
* Update gptneox-main.cpp
* constants.py : special tokens
* gguf.py : accumulate kv and tensor info data + special tokens
* convert-gptneox-h5-to-gguf.py : accumulate kv and ti + special tokens
* gguf : gguf counterpart of llama-util.h
* gguf-util.h : update note
* convert-llama-h5-to-gguf.py : accumulate kv / ti + special tokens
* convert-llama-h5-to-gguf.py : special tokens
* Delete gptneox-common.cpp
* Delete gptneox-common.h
* convert-gptneox-h5-to-gguf.py : gpt2bpe tokenizer
* gptneox-main.cpp : gpt2 bpe tokenizer
* gpt2 bpe tokenizer (handles merges and unicode)
* Makefile : remove gptneox-common
* gguf.py : bytesarray for gpt2bpe tokenizer
* cmpnct_gpt2bpe.hpp : comments
* gguf.py : use custom alignment if present
* gguf : minor stuff
* Update gptneox-main.cpp
* map tensor names
* convert-gptneox-h5-to-gguf.py : map tensor names
* convert-llama-h5-to-gguf.py : map tensor names
* gptneox-main.cpp : map tensor names
* gguf : start implementing libllama in GGUF (WIP)
* gguf : start implementing libllama in GGUF (WIP)
* rm binary commited by mistake
* upd .gitignore
* gguf : calculate n_mult
* gguf :  inference with 7B model working (WIP)
* gguf : rm deprecated function
* gguf : start implementing gguf_file_saver (WIP)
* gguf : start implementing gguf_file_saver (WIP)
* gguf : start implementing gguf_file_saver (WIP)
* gguf : add gguf_get_kv_type
* gguf : add gguf_get_kv_type
* gguf : write metadata in gguf_file_saver (WIP)
* gguf : write metadata in gguf_file_saver (WIP)
* gguf : write metadata in gguf_file_saver
* gguf : rm references to old file formats
* gguf : shorter name for member variable
* gguf : rm redundant method
* gguf : get rid of n_mult, read n_ff from file
* Update gguf_tensor_map.py
* Update gptneox-main.cpp
* gguf : rm references to old file magics
* gguf : start implementing quantization (WIP)
* gguf : start implementing quantization (WIP)
* gguf : start implementing quantization (WIP)
* gguf : start implementing quantization (WIP)
* gguf : start implementing quantization (WIP)
* gguf : start implementing quantization (WIP)
* gguf : quantization is working
* gguf : roper closing of file
* gguf.py : no need to convert tensors twice
* convert-gptneox-h5-to-gguf.py : no need to convert tensors twice
* convert-llama-h5-to-gguf.py : no need to convert tensors twice
* convert-gptneox-h5-to-gguf.py : simplify nbytes
* convert-llama-h5-to-gguf.py : simplify nbytes
* gptneox-main.cpp : n_layer --> n_block
* constants.py : n_layer --> n_block
* gguf.py : n_layer --> n_block
* convert-gptneox-h5-to-gguf.py : n_layer --> n_block
* convert-llama-h5-to-gguf.py : n_layer --> n_block
* gptneox-main.cpp : n_layer --> n_block
* Update gguf_tensor_map.py
* convert-gptneox-h5-to-gguf.py : load model in parts to save memory
* convert-llama-h5-to-gguf.py : load model in parts to save memory
* convert : write more metadata for LLaMA
* convert : rm quantization version
* convert-gptneox-h5-to-gguf.py : add file_type key
* gptneox-main.cpp : add file_type key
* fix conflicts
* gguf : add todos and comments
* convert-gptneox-h5-to-gguf.py : tensor name map changes
* Create gguf_namemap.py : tensor name map changes
* Delete gguf_tensor_map.py
* gptneox-main.cpp : tensor name map changes
* convert-llama-h5-to-gguf.py : fixes
* gguf.py : dont add empty strings
* simple : minor style changes
* gguf : use UNIX line ending
* Create convert-llama-7b-pth-to-gguf.py
* llama : sync gguf-llama.cpp with latest llama.cpp (#2608)
* llama : sync gguf-llama.cpp with latest llama.cpp
* minor : indentation + assert
* llama : refactor gguf_buffer and gguf_ctx_buffer
* llama : minor
* gitignore : add gptneox-main
* llama : tokenizer fixes (#2549)
* Merge tokenizer fixes into the gguf branch.
* Add test vocabularies
* convert : update convert-new.py with tokenizer fixes (#2614)
* Merge tokenizer fixes into the gguf branch.
* Add test vocabularies
* Adapt convert-new.py (and fix a clang-cl compiler error on windows)
* llama : sync gguf-llama with llama (#2613)
* llama : sync gguf-llama with llama
* tests : fix build + warnings (test-tokenizer-1 still fails)
* tests : fix wstring_convert
* convert : fix layer names
* llama : sync gguf-llama.cpp
* convert : update HF converter to new tokenizer voodoo magics
* llama : update tokenizer style
* convert-llama-h5-to-gguf.py : add token types
* constants.py : add token types
* gguf.py : add token types
* convert-llama-7b-pth-to-gguf.py : add token types
* gguf-llama.cpp :  fix n_head_kv
* convert-llama-h5-to-gguf.py : add 70b gqa support
* gguf.py : add tensor data layout
* convert-llama-h5-to-gguf.py : add tensor data layout
* convert-llama-7b-pth-to-gguf.py : add tensor data layout
* gptneox-main.cpp : add tensor data layout
* convert-llama-h5-to-gguf.py : clarify the reverse permute
* llama : refactor model loading code (#2620)
* llama : style formatting + remove helper methods
* llama : fix quantization using gguf tool
* llama : simplify gguf_file_saver
* llama : fix method names
* llama : simplify write_header()
* llama : no need to pass full file loader to the file saver
just gguf_ctx
* llama : gguf_file_saver write I32
* llama : refactor tensor names (#2622)
* gguf: update tensor names searched in quantization
* gguf : define tensor names as constants
* gguf : initial write API (not tested yet)
* gguf : write to file API (not tested)
* gguf : initial write API ready + example
* gguf : fix header write
* gguf : fixes + simplify example + add ggml_nbytes_pad()
* gguf : minor
* llama : replace gguf_file_saver with new gguf write API
* gguf : streaming support when writing files
* gguf : remove oboslete write methods
* gguf : remove obosolete gguf_get_arr_xxx API
* llama : simplify gguf_file_loader
* llama : move hparams and vocab from gguf_file_loader to llama_model_loader
* llama : merge gguf-util.h in llama.cpp
* llama : reorder definitions in .cpp to match .h
* llama : minor simplifications
* llama : refactor llama_model_loader (WIP)
wip : remove ggml_ctx from llama_model_loader
wip : merge gguf_file_loader in llama_model_loader
* llama : fix shape prints
* llama : fix Windows build + fix norm_rms_eps key
* llama : throw error on missing KV paris in model meta data
* llama : improve printing + log meta data
* llama : switch print order of meta data
---------
Co-authored-by: M. Yusuf Sarıgöz <yusufsarigoz@gmail.com>
* gguf : deduplicate (#2629)
* gguf : better type names
* dedup : CPU + Metal is working
* ggml : fix warnings about unused results
* llama.cpp : fix line feed and compiler warning
* llama : fix strncpy warning + note token_to_str does not write null
* llama : restore the original load/save session implementation
Will migrate this to GGUF in the future
* convert-llama-h5-to-gguf.py : support alt ctx param name
* ggml : assert when using ggml_mul with non-F32 src1
* examples : dedup simple
---------
Co-authored-by: klosax <131523366+klosax@users.noreply.github.com>
* gguf.py : merge all files in gguf.py
* convert-new.py : pick #2427 for HF 70B support
* examples/gguf : no need to keep q option for quantization any more
* llama.cpp : print actual model size
* llama.cpp : use ggml_elements()
* convert-new.py : output gguf (#2635)
* convert-new.py : output gguf (WIP)
* convert-new.py : add gguf key-value pairs
* llama : add hparams.ctx_train + no longer print ftype
* convert-new.py : minor fixes
* convert-new.py : vocab-only option should work now
* llama : fix tokenizer to use llama_char_to_byte
* tests : add new ggml-vocab-llama.gguf
* convert-new.py : tensor name mapping
* convert-new.py : add map for skipping tensor serialization
* convert-new.py : convert script now works
* gguf.py : pick some of the refactoring from #2644
* convert-new.py : minor fixes
* convert.py : update to support GGUF output
* Revert "ci : disable CI temporary to not waste energy"
This reverts commit 7e82d25f40.
* convert.py : n_head_kv optional and .gguf file extension
* convert.py : better always have n_head_kv and default it to n_head
* llama : sync with recent PRs on master
* editorconfig : ignore models folder
ggml-ci
* ci : update ".bin" to ".gguf" extension
ggml-ci
* llama : fix llama_model_loader memory leak
* gptneox : move as a WIP example
* llama : fix lambda capture
ggml-ci
* ggml : fix bug in gguf_set_kv
ggml-ci
* common.h : .bin --> .gguf
* quantize-stats.cpp : .bin --> .gguf
* convert.py : fix HF tensor permuting / unpacking
ggml-ci
* llama.cpp : typo
* llama : throw error if gguf fails to init from file
ggml-ci
* llama : fix tensor name grepping during quantization
ggml-ci
* gguf.py : write tensors in a single pass (#2644)
* gguf : single pass for writing tensors + refactoring writer
* gguf : single pass for writing tensors + refactoring writer
* gguf : single pass for writing tensors + refactoring writer
* gguf : style fixes in simple conversion script
* gguf : refactor gptneox conversion script
* gguf : rename h5 to hf (for HuggingFace)
* gguf : refactor pth to gguf conversion script
* gguf : rm file_type key and method
* gguf.py : fix vertical alignment
* gguf.py : indentation
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* convert-gptneox-hf-to-gguf.py : fixes
* gguf.py : gptneox mapping
* convert-llama-hf-to-gguf.py : fixes
* convert-llama-7b-pth-to-gguf.py : fixes
* ggml.h : reverse GGUF_MAGIC
* gguf.py : reverse GGUF_MAGIC
* test-tokenizer-0.cpp : fix warning
* llama.cpp : print kv general.name
* llama.cpp : get special token kv and linefeed token id
* llama : print number of tensors per type + print arch + style
* tests : update vocab file with new magic
* editorconfig : fix whitespaces
* llama : re-order functions
* llama : remove C++ API + reorganize common source in /common dir
* llama : minor API updates
* llama : avoid hardcoded special tokens
* llama : fix MPI build
ggml-ci
* llama : introduce enum llama_vocab_type + remove hardcoded string constants
* convert-falcon-hf-to-gguf.py : falcon HF --> gguf conversion, not tested
* falcon-main.cpp : falcon inference example
* convert-falcon-hf-to-gguf.py : remove extra kv
* convert-gptneox-hf-to-gguf.py : remove extra kv
* convert-llama-7b-pth-to-gguf.py : remove extra kv
* convert-llama-hf-to-gguf.py : remove extra kv
* gguf.py : fix for falcon 40b
* falcon-main.cpp : fix for falcon 40b
* convert-falcon-hf-to-gguf.py : update ref
* convert-falcon-hf-to-gguf.py : add tensor data layout
* cmpnct_gpt2bpe.hpp : fixes
* falcon-main.cpp : fixes
* gptneox-main.cpp : fixes
* cmpnct_gpt2bpe.hpp : remove non-general stuff
* Update examples/server/README.md
Co-authored-by: slaren <slarengh@gmail.com>
* cmpnct_gpt2bpe.hpp : cleanup
* convert-llama-hf-to-gguf.py : special tokens
* convert-llama-7b-pth-to-gguf.py : special tokens
* convert-permute-debug.py : permute debug print
* convert-permute-debug-master.py : permute debug for master
* convert-permute-debug.py : change permute type of attn_q
* convert.py : 70b model working (change attn_q permute)
* Delete convert-permute-debug-master.py
* Delete convert-permute-debug.py
* convert-llama-hf-to-gguf.py : fix attn_q permute
* gguf.py : fix rope scale kv
* convert-llama-hf-to-gguf.py : rope scale and added tokens
* convert-llama-7b-pth-to-gguf.py : rope scale and added tokens
* llama.cpp : use rope scale kv
* convert-llama-7b-pth-to-gguf.py : rope scale fix
* convert-llama-hf-to-gguf.py : rope scale fix
* py : fix whitespace
* gguf : add Python script to convert GGMLv3 LLaMA models to GGUF (#2682)
* First pass at converting GGMLv3 LLaMA models to GGUF
* Cleanups, better output during conversion
* Fix vocab space conversion logic
* More vocab conversion fixes
* Add description to converted GGUF files
* Improve help text, expand warning
* Allow specifying name and description for output GGUF
* Allow overriding vocab and hyperparams from original model metadata
* Use correct params override var name
* Fix wrong type size for Q8_K
Better handling of original style metadata
* Set default value for gguf add_tensor raw_shape KW arg
* llama : improve token type support (#2668)
* Merge tokenizer fixes into the gguf branch.
* Add test vocabularies
* Adapt convert-new.py (and fix a clang-cl compiler error on windows)
* Improved tokenizer test
But does it work on MacOS?
* Improve token type support
- Added @klosax code to convert.py
- Improved token type support in vocabulary
* Exclude platform dependent tests
* More sentencepiece compatibility by eliminating magic numbers
* Restored accidentally removed comment
* llama : add API for token type
ggml-ci
* tests : use new tokenizer type API (#2692)
* Merge tokenizer fixes into the gguf branch.
* Add test vocabularies
* Adapt convert-new.py (and fix a clang-cl compiler error on windows)
* Improved tokenizer test
But does it work on MacOS?
* Improve token type support
- Added @klosax code to convert.py
- Improved token type support in vocabulary
* Exclude platform dependent tests
* More sentencepiece compatibility by eliminating magic numbers
* Restored accidentally removed comment
* Improve commentary
* Use token type API in test-tokenizer-1.cpp
* py : cosmetics
* readme : add notice about new file format
ggml-ci
---------
Co-authored-by: M. Yusuf Sarıgöz <yusufsarigoz@gmail.com>
Co-authored-by: klosax <131523366+klosax@users.noreply.github.com>
Co-authored-by: goerch <jhr.walter@t-online.de>
Co-authored-by: slaren <slarengh@gmail.com>
Co-authored-by: Kerfuffle <44031344+KerfuffleV2@users.noreply.github.com>
		
	
		
			
				
	
	
		
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			188 lines
		
	
	
		
			6.2 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
| #include "build-info.h"
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| 
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| #include "llama.h"
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| 
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| #include <cstdio>
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| #include <cstring>
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| #include <vector>
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| #include <string>
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| 
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| struct quant_option {
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|     std::string name;
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|     llama_ftype ftype;
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|     std::string desc;
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| };
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| 
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| static const std::vector<struct quant_option> QUANT_OPTIONS = {
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|     { "Q4_0",   LLAMA_FTYPE_MOSTLY_Q4_0,   " 3.50G, +0.2499 ppl @ 7B", },
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|     { "Q4_1",   LLAMA_FTYPE_MOSTLY_Q4_1,   " 3.90G, +0.1846 ppl @ 7B", },
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|     { "Q5_0",   LLAMA_FTYPE_MOSTLY_Q5_0,   " 4.30G, +0.0796 ppl @ 7B", },
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|     { "Q5_1",   LLAMA_FTYPE_MOSTLY_Q5_1,   " 4.70G, +0.0415 ppl @ 7B", },
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| #ifdef GGML_USE_K_QUANTS
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|     { "Q2_K",   LLAMA_FTYPE_MOSTLY_Q2_K,   " 2.67G, +0.8698 ppl @ 7B", },
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|     { "Q3_K",   LLAMA_FTYPE_MOSTLY_Q3_K_M, "alias for Q3_K_M" },
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|     { "Q3_K_S", LLAMA_FTYPE_MOSTLY_Q3_K_S, " 2.75G, +0.5505 ppl @ 7B", },
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|     { "Q3_K_M", LLAMA_FTYPE_MOSTLY_Q3_K_M, " 3.06G, +0.2437 ppl @ 7B", },
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|     { "Q3_K_L", LLAMA_FTYPE_MOSTLY_Q3_K_L, " 3.35G, +0.1803 ppl @ 7B", },
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|     { "Q4_K",   LLAMA_FTYPE_MOSTLY_Q4_K_M, "alias for Q4_K_M", },
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|     { "Q4_K_S", LLAMA_FTYPE_MOSTLY_Q4_K_S, " 3.56G, +0.1149 ppl @ 7B", },
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|     { "Q4_K_M", LLAMA_FTYPE_MOSTLY_Q4_K_M, " 3.80G, +0.0535 ppl @ 7B", },
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|     { "Q5_K",   LLAMA_FTYPE_MOSTLY_Q5_K_M, "alias for Q5_K_M", },
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|     { "Q5_K_S", LLAMA_FTYPE_MOSTLY_Q5_K_S, " 4.33G, +0.0353 ppl @ 7B", },
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|     { "Q5_K_M", LLAMA_FTYPE_MOSTLY_Q5_K_M, " 4.45G, +0.0142 ppl @ 7B", },
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|     { "Q6_K",   LLAMA_FTYPE_MOSTLY_Q6_K,   " 5.15G, +0.0044 ppl @ 7B", },
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| #endif
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|     { "Q8_0",   LLAMA_FTYPE_MOSTLY_Q8_0,   " 6.70G, +0.0004 ppl @ 7B", },
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|     { "F16",    LLAMA_FTYPE_MOSTLY_F16,    "13.00G              @ 7B", },
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|     { "F32",    LLAMA_FTYPE_ALL_F32,       "26.00G              @ 7B", },
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| };
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| 
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| 
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| bool try_parse_ftype(const std::string & ftype_str_in, llama_ftype & ftype, std::string & ftype_str_out) {
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|     std::string ftype_str;
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| 
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|     for (auto ch : ftype_str_in) {
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|         ftype_str.push_back(std::toupper(ch));
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|     }
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|     for (auto & it : QUANT_OPTIONS) {
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|         if (it.name == ftype_str) {
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|             ftype = it.ftype;
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|             ftype_str_out = it.name;
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|             return true;
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|         }
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|     }
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|     try {
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|         int ftype_int = std::stoi(ftype_str);
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|         for (auto & it : QUANT_OPTIONS) {
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|             if (it.ftype == ftype_int) {
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|                 ftype = it.ftype;
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|                 ftype_str_out = it.name;
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|                 return true;
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|             }
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|         }
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|     }
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|     catch (...) {
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|         // stoi failed
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|     }
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|     return false;
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| }
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| 
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| // usage:
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| //  ./quantize [--allow-requantize] [--leave-output-tensor] models/llama/ggml-model.gguf [models/llama/ggml-model-quant.gguf] type [nthreads]
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| //
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| void usage(const char * executable) {
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|     fprintf(stderr, "usage: %s [--help] [--allow-requantize] [--leave-output-tensor] model-f32.gguf [model-quant.gguf] type [nthreads]\n\n", executable);
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|     fprintf(stderr, "  --allow-requantize: Allows requantizing tensors that have already been quantized. Warning: This can severely reduce quality compared to quantizing from 16bit or 32bit\n");
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|     fprintf(stderr, "  --leave-output-tensor: Will leave output.weight un(re)quantized. Increases model size but may also increase quality, especially when requantizing\n");
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|     fprintf(stderr, "\nAllowed quantization types:\n");
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|     for (auto & it : QUANT_OPTIONS) {
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|         printf("  %2d  or  %-6s : %s\n", it.ftype, it.name.c_str(), it.desc.c_str());
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|     }
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|     exit(1);
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| }
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| 
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| int main(int argc, char ** argv) {
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|     if (argc < 3) {
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|         usage(argv[0]);
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|     }
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| 
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|     llama_model_quantize_params params = llama_model_quantize_default_params();
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| 
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|     int arg_idx = 1;
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| 
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|     for (; arg_idx < argc && strncmp(argv[arg_idx], "--", 2) == 0; arg_idx++) {
 | |
|         if (strcmp(argv[arg_idx], "--leave-output-tensor") == 0) {
 | |
|             params.quantize_output_tensor = false;
 | |
|         } else if (strcmp(argv[arg_idx], "--allow-requantize") == 0) {
 | |
|             params.allow_requantize = true;
 | |
|         } else {
 | |
|             usage(argv[0]);
 | |
|         }
 | |
|     }
 | |
| 
 | |
|     if (argc - arg_idx < 3) {
 | |
|         usage(argv[0]);
 | |
|     }
 | |
| 
 | |
|     llama_backend_init(false);
 | |
| 
 | |
|     // parse command line arguments
 | |
|     const std::string fname_inp = argv[arg_idx];
 | |
|     arg_idx++;
 | |
|     std::string fname_out;
 | |
| 
 | |
|     std::string ftype_str;
 | |
|     if (try_parse_ftype(argv[arg_idx], params.ftype, ftype_str)) {
 | |
|         std::string fpath;
 | |
|         const size_t pos = fname_inp.find_last_of('/');
 | |
|         if (pos != std::string::npos) {
 | |
|             fpath = fname_inp.substr(0, pos + 1);
 | |
|         }
 | |
|         // export as [inp path]/ggml-model-[ftype].gguf
 | |
|         fname_out = fpath + "ggml-model-" + ftype_str + ".gguf";
 | |
|         arg_idx++;
 | |
|     }
 | |
|     else {
 | |
|         fname_out = argv[arg_idx];
 | |
|         arg_idx++;
 | |
| 
 | |
|         if (argc <= arg_idx) {
 | |
|             fprintf(stderr, "%s: missing ftype\n", __func__);
 | |
|             return 1;
 | |
|         }
 | |
|         if (!try_parse_ftype(argv[arg_idx], params.ftype, ftype_str)) {
 | |
|             fprintf(stderr, "%s: invalid ftype '%s'\n", __func__, argv[3]);
 | |
|             return 1;
 | |
|         }
 | |
|         arg_idx++;
 | |
|     }
 | |
| 
 | |
|     // parse nthreads
 | |
|     if (argc > arg_idx) {
 | |
|         try {
 | |
|             params.nthread = std::stoi(argv[arg_idx]);
 | |
|         }
 | |
|         catch (const std::exception & e) {
 | |
|             fprintf(stderr, "%s: invalid nthread '%s' (%s)\n", __func__, argv[arg_idx], e.what());
 | |
|             return 1;
 | |
|         }
 | |
|     }
 | |
| 
 | |
|     fprintf(stderr, "%s: build = %d (%s)\n", __func__, BUILD_NUMBER, BUILD_COMMIT);
 | |
| 
 | |
|     fprintf(stderr, "%s: quantizing '%s' to '%s' as %s", __func__, fname_inp.c_str(), fname_out.c_str(), ftype_str.c_str());
 | |
|     if (params.nthread > 0) {
 | |
|         fprintf(stderr, " using %d threads", params.nthread);
 | |
|     }
 | |
|     fprintf(stderr, "\n");
 | |
| 
 | |
|     const int64_t t_main_start_us = llama_time_us();
 | |
| 
 | |
|     int64_t t_quantize_us = 0;
 | |
| 
 | |
|     // load the model
 | |
|     {
 | |
|         const int64_t t_start_us = llama_time_us();
 | |
| 
 | |
|         if (llama_model_quantize(fname_inp.c_str(), fname_out.c_str(), ¶ms)) {
 | |
|             fprintf(stderr, "%s: failed to quantize model from '%s'\n", __func__, fname_inp.c_str());
 | |
|             return 1;
 | |
|         }
 | |
| 
 | |
|         t_quantize_us = llama_time_us() - t_start_us;
 | |
|     }
 | |
| 
 | |
|     // report timing
 | |
|     {
 | |
|         const int64_t t_main_end_us = llama_time_us();
 | |
| 
 | |
|         printf("\n");
 | |
|         printf("%s: quantize time = %8.2f ms\n", __func__, t_quantize_us/1000.0);
 | |
|         printf("%s:    total time = %8.2f ms\n", __func__, (t_main_end_us - t_main_start_us)/1000.0);
 | |
|     }
 | |
| 
 | |
|     llama_backend_free();
 | |
| 
 | |
|     return 0;
 | |
| }
 |