Age | Commit message (Collapse) | Author |
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preceeding -> preceding
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* ggml : fix soft max out-of-bounds access
ggml-ci
* ggml : reuse ggml_get_n_tasks() in ggml_graph_plan()
ggml-ci
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ggml-ci
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(cherry picked from commit Mozilla-Ocho/llamafile@e8c92bcb84ae3bcbf0d617b7ee6a5413bcbd58af)
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* llama : pad KV cache size to 32
* metal : try to improve batched decoding
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* Fix token_to_piece implementation in Swift
* Fix errors
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* Support attention_bias on LLaMA architecture
QKVO bias, should fix InternLM (https://github.com/ggerganov/llama.cpp/issues/3133) and works for LLaMAfied Qwen models (https://github.com/ggerganov/llama.cpp/pull/3743#issuecomment-1825923608).
* check existence of qkvo bias while loading llama models
Tested on LLaMA2, CUDA and CPU.
* Update llama.cpp
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* enable qwen to llama.cpp
* llama : do not GPU split bias tensors
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Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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happens with multi-threaded quantization of Qwen-72B
ggml-ci
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This commit adds a requirements file for the convert-hf-to-gguf.py
script, and also add the torch and transformers packages to it.
The motivation for this is that currently running convert-hf-to-gguf.py
will produce the following error:
```console
$ python3 -m venv venv
$ source venv/bin/activate
(venv) $ pip install -r requirements.txt
Collecting numpy==1.24.4
Collecting sentencepiece==0.1.98
Collecting gguf>=0.1.0
Installing collected packages: sentencepiece, numpy, gguf
Successfully installed gguf-0.5.1 numpy-1.24.4 sentencepiece-0.1.98
(venv) $ python convert-hf-to-gguf.py --help
Traceback (most recent call last):
File "llama.cpp/convert-hf-to-gguf.py", line 16, in <module>
import torch
ModuleNotFoundError: No module named 'torch'
```
With this commit, and using requirements-hf-to-gguf.txt instead of
requirements.txt, the script can be run and shows the help output.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
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* metal : implement soft_max_ext
* cuda : implement soft_max_ext
* ggml : implement soft_max_ext (CPU)
* batched-bench : print threads
ggml-ci
* metal : simplify soft_max encoding
ggml-ci
* cuda : use 512 threads for soft_max instead of 32
* ggml : update soft max cpu
* cuda : do warp-based block reduce
* cuda : increase max block size to 1024
* cuda : fix warp reduction initialization of shared mem
* metal : warp-based reduction for soft max kernel
* metal : warp-based reduce for rms_norm
* metal : simplify soft max kernel
ggml-ci
* alloc : fix build with debug
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* * add --log-disable to disable logging to file in the server example
* * typo fix
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* * add multiprompt support
* * cleanup
* * more cleanup
* * remove atomicity of id_gen, and change lock_guard to unique_lock on completion requests
* * remove all references to mutex_multitasks
* Update examples/server/server.cpp
Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
* Update examples/server/server.cpp
Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
* Update examples/server/server.cpp
Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
* Update examples/server/server.cpp
Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
* * change to set
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Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
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Co-authored-by: Will Findley <findley@gmail.com>
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* cmake : fix joining of REAL_GIT_DIR
* fix includes with help from include-what-you-use
* make : remove unneeded deps and add test-rope target
* fix C includes in C++ source files
* Revert "fix includes with help from include-what-you-use"
This reverts commit 635e9fadfd516d4604a0fecf4a854bfb25ad17ae.
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* ShareGPT4 compatibility (vision encoder only loading)
Load only a CLIP vision encoder (as supplied by ShareGPT finetunes)
Corrects the argument parsing for --img_mean and --img_std (which were previously not parsed but attempted to access)
Defines defaults for img_mean and img_std which are equal to the llava 1.5 CLIP encoder, so you do not have to provide them
* Update convert-image-encoder-to-gguf.py
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* main : Call llama_log_set to use LOG_TEE
* tabs to spaces
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* fix: readme
* chore: resolve comments
* chore: resolve comments
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docs: update how to run
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llama.cpp uses GitHub Actions, not Gitlab Actions.
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* llama: fix alignment of general.name in print meta
This commit fixes the alignment of the general.name field in the
llm_load_print_meta function.
Currently the output looks like this:
```console
llm_load_print_meta: model ftype = mostly Q4_0
llm_load_print_meta: model params = 13.02 B
llm_load_print_meta: model size = 6.86 GiB (4.53 BPW)
llm_load_print_meta: general.name = LLaMA v2
```
And with this commit it looks like this:
```console
llm_load_print_meta: model ftype = mostly Q4_0
llm_load_print_meta: model params = 13.02 B
llm_load_print_meta: model size = 6.86 GiB (4.53 BPW)
llm_load_print_meta: general.name = LLaMA v2
```
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* llama: fix alignment of special tokens
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
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Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
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Typical sampling was broken because after copying new_candidates into canditates, the "sorted" bool is left at "true", but the new data is no longer sorted according to probability. Patch to set "sorted" to false.
Test: Generating with temp=0.0001 (approx. argmax) should generate the same sequence at typical>=1.0 and typical=0.9999 (approx. disabled, but enters the typical sampling codepath).
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* fix oai proxy
fix generation not stoped while bot stop talking in chat mode
fix possible `slot_id` not exist
response for cors (and pre flight)
* oai proxy: workaround for some client (such as Chatbox)
* use stop as separator to replace hardcoded `\n`
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offload checks in llama.cpp (#4240)
* ggml : use blas even if src0 is not F32
* llama : use n_threads_batch only when n_tokens >= 32
ggml-ci
* llama : revert n_threads_batch logic
ggml-ci
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(#3970)
* Split CPP generation from build-info query
* Remove blank lines
* Add BUILD_SHARED_LIBS option
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* copy to llama.cpp as subdir
* attempt enabling metal, fails
* ggml metal compiles!
* Update README.md
* initial conversion to new format, utf8 errors?
* bug fixes, but now has an invalid memory access :(
* added O3, now has insufficient memory access
* begin sync with master
* update to match latest code, new errors
* fixed it!
* fix for loop conditionals, increase result size
* fix current workflow errors
* attempt a llama.swiftui workflow
* Update .github/workflows/build.yml
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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* lookahead : init
* lookahead : generate and store n-grams
* lookahead : use loop instead recursion to generate n-grams
* lookahead : initial working implementation
* lookahead : filter repeating n-grams
* lookahead : use deterministic init
* lookahead : add to Makefile
* lookahead : fix a bug in the seq_id of the lookahead tokens
* lookahead : add comments
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Co-authored-by: slaren <slarengh@gmail.com>
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get the correct n_orig_ctx in metal
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* Use mmap in torch load, prefer .bin files when loading
* Revert .bin > .safetensors preference
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* reserve space for codepoints
* improvement for the appended 0
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* Add openai-compatible POST /v1/chat/completions API endpoint to server example
* fix code style
* Update server README.md
* Improve server README.md
* Fix server.cpp code style according to review
* server : some style changes
* server : indentation
* server : enable special tokens during tokenization by default
* server : minor code style
* server : change random string generator
* straightforward /v1/models endpoint
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Co-authored-by: kir-gadjello <111190790+kir-gadjello@users.noreply.github.com>
Co-authored-by: Tobi Lütke <tobi@Tobis-MacBook-Pro.local>
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* ggml-cuda : support stablelm rope
* remove unused freq_base kernel parameter
* add n_dims parameter to llm_build_k_shift, default to n_rot via overload
* llama : fix llm_build_k_shift args
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Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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