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guidance scale (#2280)
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A fix in Makefile for FreeBSD users. In the platfrom x86_64 is amd64. This fix resolve compilation using CFLAGS and CXXFLAGS with -march=native and -mtune=native
Add two examples for interactive mode using Llama2 models (thx TheBloke for models)
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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* Miku.sh: Set default model to llama-2-7b-chat
* Miku.sh: Set ctx_size to 4096
* Miku.sh: Add in-prefix/in-suffix opts
* Miku.sh: Switch sampler to mirostat_v2 and tiny prompt improvements
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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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* ci : run ctest
ggml-ci
* ci : add open llama 3B-v2 tests
ggml-ci
* ci : disable wget progress output
ggml-ci
* ci : add open llama 3B-v2 tg tests for q4 and q5 quantizations
ggml-ci
* tests : try to fix tail free sampling test
ggml-ci
* ci : add K-quants
ggml-ci
* ci : add short perplexity tests
ggml-ci
* ci : add README.md
* ppl : add --chunks argument to limit max number of chunks
ggml-ci
* ci : update README
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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
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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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* Add ggml changes
* Update train-text-from-scratch for change
* mpi : adapt to new ggml_tensor->src
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Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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* Initial implementation
* Remove debug print
* Restore signature of llama_init_from_gpt_params
* Free guidance context
* Make freeing of guidance_ctx conditional
* Make Classifier-Free Guidance a sampling function
* Correct typo. CFG already means context-free grammar.
* Record sampling time in llama_sample_classifier_free_guidance
* Shift all values by the max value before applying logsoftmax
* Fix styling based on review
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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)
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Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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* ggml_graph_compute: deprecate using ggml_context, try resolve issue #287
* rewrite: no longer consider backward compitability; plan and make_plan
* minor: rename ctx as plan; const
* remove ggml_graph_compute from tests/test-grad0.c, but current change breaks backward
* add static ggml_graph_compute_sugar()
* minor: update comments
* reusable buffers
* ggml : more consistent naming + metal fixes
* ggml : fix docs
* tests : disable grad / opt + minor naming changes
* ggml : add ggml_graph_compute_with_ctx()
- backwards compatible API
- deduplicates a lot of copy-paste
* ci : enable test-grad0
* examples : factor out plan allocation into a helper function
* llama : factor out plan stuff into a helper function
* ci : fix env
* llama : fix duplicate symbols + refactor example benchmark
* ggml : remove obsolete assert + refactor n_tasks section
* ggml : fix indentation in switch
* llama : avoid unnecessary bool
* ggml : remove comments from source file and match order in header
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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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The original file name, `ggml-alpaca-7b-q4.bin`, implied the first-generation GGML. After the breaking changes (mentioned in https://github.com/ggerganov/llama.cpp/issues/382), `llama.cpp` requires GGML V3 now. Those model files are named `*ggmlv3*.bin`. We should change the example to an actually working model file, so that this thing is more likely to run out-of-the-box for more people, and less people would waste time downloading the old Alpaca model.
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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
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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
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Co-authored-by: Jesse Johnson <thatguy@jessejojojohnson.com>
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* Generalize quantize_fns for simpler FP16 handling
* Remove call to ggml_cuda_mul_mat_get_wsize
* ci : disable FMA for mac os actions
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Co-authored-by: Georgi Gerganov <ggerganov@gmail.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
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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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* add interface for float input
* fixed inpL shape and type
* add examples of input floats
* add test example for embd input
* fixed sampling
* add free for context
* fixed add end condition for generating
* add examples for llava.py
* add READMD for llava.py
* add READMD for llava.py
* add example of PandaGPT
* refactor the interface and fixed the styles
* add cmake build for embd-input
* add cmake build for embd-input
* Add MiniGPT-4 example
* change the order of the args of llama_eval_internal
* fix ci error
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(#1988)
* Clean up compiler warnings in train-text
Some brackets to disambiguate order of operations
* Increase GGML_MAX_NAME
Avoiding strncpy danger in train-text-from-scratch and reducing potential future name length issues
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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
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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
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Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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* Add back embedding feature
* Update README
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Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
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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
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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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Small, non-functional changes were made to non-compliant files.
These include breaking up long lines, whitespace sanitation and
unused import removal.
Maximum line length in python files was set to a generous 125 chars,
in order to minimize number of changes needed in scripts and general
annoyance. The "txt" prompts directory is excluded from the checks
as it may contain oddly formatted files and strings for a good reason.
Signed-off-by: Jiri Podivin <jpodivin@gmail.com>
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We probably want to train using just the text of Shakespeare instead of the html of the page displaying his work.
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* Create `simple.cpp`
* minimalist example `CMakeLists.txt`
* Update Makefile for minimalist example
* remove 273: Trailing whitespace
* removed trailing white spaces simple.cpp
* typo and comments simple.cpp
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Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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MinGW libstdc++ may define `NOMINMAX` unconditionally. This fixes the case when it is already defined.
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