Infinite context loop might as well trigger an infinite loop of context
shifting if the model hallucinates and does not stop answering.
This has the unpleasant effect that the predicion never terminates,
which is the case especially on small models which tends to hallucinate.
Workarounds https://github.com/mudler/LocalAI/issues/1333 by removing
context-shifting.
See also upstream issue: https://github.com/ggerganov/llama.cpp/issues/3969
* feat(refactor): refactor config and input reading
* feat(tts): read config file for TTS
* examples(kubernetes): Add simple deployment example
* examples(kubernetes): Add simple deployment for intel arc
* docs(sycl): add sycl example
* feat(tts): do not always pick a first model
* fixups to run vall-e-x on container
* Correctly resolve backend
* cleanup backends
* switch image to ubuntu 22.04
* adapt commands for ubuntu
* transformers cleanup
* no contrib on ubuntu
* Change test model to gguf
* ci: disable bark tests (too cpu-intensive)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* cleanup
* refinements
* use intel base image
* Makefile: Add docker targets
* Change test model
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(transformers): support also text generation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* embedded: set seed -1
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Certain backends as vall-e-x are not meant to be used as a library, so
we want to start the process in the same folder where the backend and
all the assets are fixes#1394
* feat(conda): share env between diffusers and bark
* Detect if env already exists
* share diffusers and petals
* tests: add petals
* Use smaller model for tests with petals
* test only model load on petals
* tests(petals): run only load model tests
* Revert "test only model load on petals"
This reverts commit 111cfa97f1.
* move transformers and sentencetransformers to common env
* Share also transformers-musicgen
* feat(img2vid): Initial support for img2vid
* doc(SD): fix SDXL Example
* Minor fixups for img2vid
* docs(img2img): fix example curl call
* feat(txt2vid): initial support
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
* diffusers: be retro-compatible with CUDA settings
* docs(img2vid, txt2vid): examples
* Add notice on docs
---------
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
* Use cuda in transformers if available
tensorflow probably needs a different check.
Signed-off-by: Erich Schubert <kno10@users.noreply.github.com>
* feat: expose CUDA at top level
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* tests: add to tests and create workflow for py extra backends
* doc: update note on how to use core images
---------
Signed-off-by: Erich Schubert <kno10@users.noreply.github.com>
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Erich Schubert <kno10@users.noreply.github.com>
* Update docs for new requirements.txt path
Signed-off-by: Marcus Köhler <khler.marcus@gmail.com>
* Fix typo (.PONY -> .PHONY) in python backend makefiles
Signed-off-by: Marcus Köhler <khler.marcus@gmail.com>
---------
Signed-off-by: Marcus Köhler <khler.marcus@gmail.com>
* Fix python header comments for some extra gRPC backends
When a Python script is to be executed directly via exec(3), either the platform knows how to execute
the file itself (i.e. special configuration is necessary) or the first line
contains a shebang (#!) specifying the interpreter to run it (similar to
shell scripts).
The shebang MUST be on the first line for the script to work on all platforms,
so any header comments need to be in the lines following it. Otherwise
executing these scripts as extra backends will yield an "exec format
error" message.
Changes:
* Move introductory comments below the shebang line
* Change header comment in transformers.py to refer to the correct
python module
Signed-off-by: Marcus Köhler <khler.marcus@gmail.com>
* Make header comment in ttsbark.py more specific
Signed-off-by: Marcus Köhler <khler.marcus@gmail.com>
---------
Signed-off-by: Marcus Köhler <khler.marcus@gmail.com>
* Update huggingface.py
Switch SentenceTransformer for AutoModel in order to set trust_remote_code needed to use the encode method with embeddings models like jinai-v2
Signed-off-by: Lucas Hänke de Cansino <lhc@next-boss.eu>
* feat(transformers): split in separate backend
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Lucas Hänke de Cansino <lhc@next-boss.eu>
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Lucas Hänke de Cansino <lhc@next-boss.eu>
* refactor: rename llama-stable to llama-ggml
* Makefile: get sources in sources/
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fixup path
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fixup sources
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fixups sd
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* update SD
* fixup
* fixup: create piper libdir also when not built
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix make target on linux test
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactor: move backends into the backends directory
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactor: move main close to implementation for every backend
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
