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* 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 7e82d25f40386540c2c15226300ad998ecd871ea.
* 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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* server : update xxd usage for older versions compatibility
* remove unused $func
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* support for templates in browser LocalStorage
* sync accepted #2409 fix from upstream
* convert autosave invocation to useEffect
* Apply suggestions from code review
Co-authored-by: Jhen-Jie Hong <iainst0409@gmail.com>
* Regen index.html.cpp, suggested from code review
---------
Co-authored-by: Jhen-Jie Hong <iainst0409@gmail.com>
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fixes #2611
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(#2588)
* server : implement json-schema-to-grammar.mjs by follow python impl
* server : add grammar support in chat.mjs
* server : implement grammer param in the UI
* server : generate .hpp
* server : remove trailing whitespaces
* server : generate .hpp
* server : fix sort of prop pairs
* server : optimize regex & iteration
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* server: fixed wrong variable name in timing json
* remove redunct entry
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* Allow passing grammar to completion endpoint
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* Fixing race condition in server.cpp and partial stream handling in completion.js
* Reverting assert edits.
* Adding newline to eof
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* server : Support dark mode
So it respects user system light / dark settings.
* Update index.html.hpp by running ./deps.sh
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* add: server chat mode with llama2
* fix: remove the unnecessary last \n
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* escape HTML in webchat
* add amp
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* makefile: correct deps for server
* server: tighten settings layout a little
* server: expose all currently configured generation params in UI
* server: expose remaining generation params, for the adventurous
* server: embetter mirostat fields
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* Add gqa parameter support to the server
* Change help from stderr to stdout
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* make : fix embdinput library and server examples building on MSYS2
* cmake : fix server example building on MSYS2
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fix #2252
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* Implement customizable RoPE
The original RoPE has pre-defined parameters
theta_i = 10000^(−2(i−1)/d), for i in [1, 2, ..., d/2]
Our customizable RoPE, ggml_rope_custom_inplace, uses
theta_i = scale * base^(−2(i−1)/d), for i in [1, 2, ..., d/2]
with the default matches the original
scale = 1.0
base = 10000
The new command line arguments
--rope-freq-base
--rope-freq-scale
set the two new RoPE parameter.
Recent researches show changing these two parameters extends the context limit with minimal loss.
1. Extending Context to 8K
kaiokendev
https://kaiokendev.github.io/til#extending-context-to-8k
2. Extending Context Window of Large Language Models via Positional Interpolation
Shouyuan Chen, Sherman Wong, Liangjian Chen, Yuandong Tian
https://arxiv.org/abs/2306.15595
3. NTK-Aware Scaled RoPE allows LLaMA models to have extended (8k+) context size without any fine-tuning and minimal perplexity degradation.
https://www.reddit.com/user/bloc97
https://www.reddit.com/r/LocalLLaMA/comments/14lz7j5/ntkaware_scaled_rope_allows_llama_models_to_have/
For the bold, try adding the following command line parameters to your favorite model:
-c 16384 --rope-freq-base 80000 --rope-freq-scale 0.5
* ggml-metal: fix custom rope
* common: fix argument names in help
* llama: increase MEM_REQ_EVAL for MODEL_3B
It avoids crashing for quantized weights on CPU.
Better ways to calculate the required buffer size would be better.
* llama: make MEM_REQ_EVAL depend on n_ctx
* server: use proper Content-Type in curl examples
Without the header Content-Type: application/json, curl will POST with
Content-Type: application/x-www-form-urlencoded
Though our simple server doesn't care, the httplib.h used has a limit
with CPPHTTPLIB_FORM_URL_ENCODED_PAYLOAD_MAX_LENGTH 8192
With Content-Type: application/json, we can send large json data.
* style : minor fixes, mostly indentations
* ggml : fix asserts
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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Has perf regression when mlock is used.
This reverts commit 2347463201a9f4159ae95b737e1544dd300569c8.
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* Support using mmap when applying LoRA
* Fix Linux
* Update comment to reflect the support lora with mmap
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* MPI support, first cut
* fix warnings, update README
* fixes
* wrap includes
* PR comments
* Update CMakeLists.txt
* Add GH workflow, fix test
* Add info to README
* mpi : trying to move more MPI stuff into ggml-mpi (WIP) (#2099)
* mpi : add names for layer inputs + prep ggml_mpi_graph_compute()
* mpi : move all MPI logic into ggml-mpi
Not tested yet
* mpi : various fixes - communication now works but results are wrong
* mpi : fix output tensor after MPI compute (still not working)
* mpi : fix inference
* mpi : minor
* Add OpenMPI to GH action
* [mpi] continue-on-error: true
* mpi : fix after master merge
* [mpi] Link MPI C++ libraries to fix OpenMPI
* tests : fix new llama_backend API
* [mpi] use MPI_INT32_T
* mpi : factor out recv / send in functions and reuse
* mpi : extend API to allow usage with outer backends (e.g. Metal)
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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1. guess n_layers;
2. relax warnings on context size;
3. add a note that its derivations are also supported.
Co-authored-by: Judd <foldl@boxvest.com>
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* use javascript generators as much cleaner API
Also add ways to access completion as promise and EventSource
* export llama_timings as struct and expose them in server
* update readme, update baked includes
* llama : uniform variable names + struct init
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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* Update server instructions for web front end
* Update server README
* Remove duplicate OAI instructions
* Fix duplicate text
---------
Co-authored-by: Jesse Johnson <thatguy@jessejojojohnson.com>
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Co-authored-by: Jesse Johnson <thatguy@jessejojojohnson.com>
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* add api_like_OAI.py
* add evaluated token count to server
* add /v1/ endpoints binding
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* expose simple web interface on root domain
* embed index and add --path for choosing static dir
* allow server to multithread
because web browsers send a lot of garbage requests we want the server
to multithread when serving 404s for favicon's etc. To avoid blowing up
llama we just take a mutex when it's invoked.
* let's try this with the xxd tool instead and see if msvc is happier with that
* enable server in Makefiles
* add /completion.js file to make it easy to use the server from js
* slightly nicer css
* rework state management into session, expose historyTemplate to settings
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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* server: add option to output probabilities for completion
* server: fix issue when handling probability output for incomplete tokens for multibyte character generation
* server: fix llama_sample_top_k order
* examples/common.h: put all bool variables in gpt_params together
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* Use unsigned for random seed. Keep -1 as the value to use a time based seed.
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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* detect NUMA systems and pin work threads to nodes (linux)
* disable mmap prefetch/readahead for NUMA systems
* avoid sending finalize op to thread pool if it does nothing
* silence robot
* fix args
* make --numa a param
* recommendation that n_nodes evenly divide n_threads did not warrant such aggressive enforcement
* lower synchronization overhead
* statically allocate
* move numa state to g_state
* add description for --numa
* ggml : minor style changes
* ggml : minor style + try fix sanitizer build
* llama : allow to initialize backend with NUMA support
* llama : avoid ggml include in llama-util.h
* ggml : style / formatting
* ggml : fix handling of ops with n_threads > n_tasks > 1
* server : utilize numa parameter
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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Co-authored-by: anon <anon@example.org>
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* llama : make model stateless and context stateful
* llama : minor cleanup
* llama : update internal API declaration
* Apply suggestions from code review
fix style
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Missing model memory release
* Fix style
* Add deprecated warning for public API function llama_init_from_file
* Update public API use cases: move away from deprecated llama_init_from_file
* Deprecate public API function llama_apply_lora_from_file
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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* Add back embedding feature
* Update README
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A major rewrite for the server example.
Note that if you have built something on the previous server API, it will probably be incompatible.
Check out the examples for how a typical chat app could work.
This took a lot of effort, there are 24 PR's closed in the submitter's repo alone, over 160 commits and a lot of comments and testing.
Summary of the changes:
- adds missing generation parameters: tfs_z, typical_p, repeat_last_n, repeat_penalty, presence_penalty, frequency_penalty, mirostat, penalize_nl, seed, ignore_eos
- applies missing top k sampler
- removes interactive mode/terminal-like behavior, removes exclude parameter
- moves threads and batch size to server command-line parameters
- adds LoRA loading and matches command line parameters with main example
- fixes stopping on EOS token and with the specified token amount with n_predict
- adds server timeouts, host, and port settings
- adds expanded generation complete response; adds generation settings, stop reason, prompt truncated, model used, and final text
- sets defaults for unspecified parameters between requests
- removes /next-token endpoint and as_loop parameter, adds stream parameter and server-sent events for streaming
- adds CORS headers to responses
- adds request logging, exception printing and optional verbose logging
- adds better stopping words handling when matching multiple tokens and while streaming, or when it finishes on a partial stop string
- adds printing an error when it can't bind to the host/port specified
- fixes multi-byte character handling and replaces invalid UTF-8 characters on responses
- prints timing and build info on startup
- adds logit bias to request parameters
- removes embedding mode
- updates documentation; adds streaming Node.js and Bash examples
- fixes code formatting
- sets server threads to 1 since the current global state doesn't work well with simultaneous requests
- adds truncation of the input prompt and better context reset
- removes token limit from the input prompt
- significantly simplified the logic and removed a lot of variables
---------
Co-authored-by: anon998 <131767832+anon998@users.noreply.github.com>
Co-authored-by: Henri Vasserman <henv@hot.ee>
Co-authored-by: Felix Hellmann <privat@cirk2.de>
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
Co-authored-by: Lesaun Harvey <Lesaun@gmail.com>
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Explicitly include the server make instructions for C++ noobsl like me ;)
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* Fixed CUDA RoPE
* ggml_cuda_mul_mat_vec_p021
* ggml_cuda_scale
* ggml_cuda_diag_mask_inf
* ggml_is_permuted
* ggml_cuda_cpy
* flatten rows for ggml_cuda_op
* Added a --low-vram option
* Fixed Windows performance
* Fixed LLAMA_CUDA_DMMV_Y > 1 for WizardLM
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* CUDA multi GPU + scratch
ggml_cuda_compute_forward
Tensor parallelism
ggml_cuda_add
ggml_cuda_rms_norm
ggml_cuda_silu
CUDA scratch buffer
--main-gpu CLI option
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1. Add a `LLAMA_SUPPORTS_GPU_OFFLOAD` define to `llama.h` (defined when compiled with CLBlast or cuBLAS)
2. Update the argument handling in the common example code to only show the `-ngl`, `--n-gpu-layers` option when GPU offload is possible.
3. Add an entry for the `-ngl`, `--n-gpu-layers` option to the `main` and `server` examples documentation
4. Update `main` and `server` examples documentation to use the new style dash separator argument format
5. Update the `server` example to use dash separators for its arguments and adds `-ngl` to `--help` (only shown when compiled with appropriate support). It will still support `--memory_f32` and `--ctx_size` for compatibility.
6. Add a warning discouraging use of `--memory-f32` for the `main` and `server` examples `--help` text as well as documentation. Rationale: https://github.com/ggerganov/llama.cpp/discussions/1593#discussioncomment-6004356
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(#1614)
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Set `LLAMA_BUILD_SERVER` in workflow so the `server` example gets build. This currently only applies to Windows builds because it seems like only Windows binary artifacts are included in releases.
Add `server` example target to `Makefile` (still uses `LLAMA_BUILD_SERVER` define and does not build by default)
Fix issue where `vdot` binary wasn't removed when running `make clean`.
Fix compile warnings in `server` example.
Add `.hpp` files to trigger workflow (the server example has one).
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* Added httplib support
* Added readme for server example
* fixed some bugs
* Fix the build error on Macbook
* changed json11 to nlohmann-json
* removed some whitespaces
* remove trailing whitespace
* added support custom prompts and more functions
* some corrections and added as cmake option
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