| Name | llm-text-generation JSON |
| Version |
0.1.1
JSON |
| download |
| home_page | None |
| Summary | Run large language models. |
| upload_time | 2024-11-27 14:13:33 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. "Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. "Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. "You" (or "Your") shall mean an individual or Legal Entity exercising permissions granted by this License. "Source" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. "Object" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types. "Work" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below). "Derivative Works" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof. "Contribution" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, "submitted" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Work, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as "Not a Contribution." "Contributor" shall mean Licensor and any individual or Legal Entity on behalf of whom a Contribution has been received by Licensor and subsequently incorporated within the Work. 2. Grant of Copyright License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. 3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed. 4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and (b) You must cause any modified files to carry prominent notices stating that You changed the files; and (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and (d) If the Work includes a "NOTICE" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License. You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. 5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions. 6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file. 7. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License. 8. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages. 9. Accepting Warranty or Additional Liability. While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability. END OF TERMS AND CONDITIONS APPENDIX: How to apply the Apache License to your work. To apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets "[]" replaced with your own identifying information. (Don't include the brackets!) The text should be enclosed in the appropriate comment syntax for the file format. We also recommend that a file or class name and description of purpose be included on the same "printed page" as the copyright notice for easier identification within third-party archives. Copyright [yyyy] [name of copyright owner] Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. |
| keywords |
nlp
text
llm
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
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|
## LLM Text Generation
Generate natural language text with large language models.
### Installation
This project requires Python 3.10 or higher.
#### From PyPI
```bash
pip install llm-text-generation
```
#### From source
```bash
git clone git@github.com:ad-freiburg/llm-text-generation.git
cd llm-text-generation
pip install -e .
```
### Usage
#### From Python
#### From command line
After installation the command `llm-gen` is available in your python environment.
It lets you use the text generation models directly from the command line.
Below are examples of how to use `llm-gen`. See `llm-gen -h` for all options.
```bash
# print version
llm-gen -v
# list available models
llm-gen -l
# by default llm-gen tries to read stdin, complete the input it got line by line
# and prints the completed lines back out
# therefore, you can for example use text generation with pipes
echo "The capital of Germany is" | llm-gen
cat "path/to/input/file.txt" | llm-gen > output.txt
# complete a string using
llm-gen -p "The capital of Germany is"
# complete a text file line by line and print the completed lines
llm-gen -f path/to/input/file.txt
# optionally specify an output file path where the completed lines are saved
llm-gen -f path/to/input/file.txt -o output.txt
# start an interactive text generation session
# where your input will be completeed and printed back out
llm-gen -i
# start a text generation server with the following endpoints:
### /models [GET] --> output: available models as json
### /info [GET] --> output: info about backend as json
### /generate [POST] input: some input text --> output: continuation of the input text
### /live [WS] websocket endpoint for live text generation (only single unbatched requests)
llm-gen --server <config_file>
### OPTIONS
### Pass the following flags to the llm-gen command to customize its behaviour
-m <model_name> # use a different text generation model than the default one
--cpu # force execution on CPU, by default a GPU is used if available
--progress # display a progress bar (always on when a file is repaired using -f)
-b <batch_size> # specify a different batch size
-batch-max-tokens <batch_max_tokens> # limit batch by a number of tokens and not by number of samples
-u # do not sort the inputs before completeing
-e <experiment_dir> # specify the path to an experiment directory to load the model from
# (equivalent to TextGenerator.from_experiment(experiment_dir) in Python API)
--force-download # force download of the text generation model even if it was already downloaded
--progress # show a progress bar while completing
--report # print a report on the runtime of the model after finishing the completion
```
> Note: When first using `llm-gen` with a pretrained model, the model needs to be downloaded, so depending on
> your internet speed the command might take considerably longer.
> Note: Loading the text generation model requires an initial startup time each time you
> invoke the `llm-gen` command. CPU startup time is around 1s, GPU startup time around 3.5s, so for small
> inputs or files you should probably pass the `--cpu` flag to force CPU execution for best performance.
> See [configs/server.yaml](configs/server.yaml) for an exemplary server configuration file.
### Documentation
#### Use pretrained model
If you just want to use this project to complete whitespaces, this is the recommended way.
```python
from llm_text_generation import TextGenerator
gen = TextGenerator.from_pretrained(
# pretrained model to load, get all available models from available_models(),
# if None, loads the default model
model=None,
# the device to run the model on
# ("cuda" by default)
device="cuda",
# optional path to a cache directory where downloaded models will be extracted to,
# if None, we check the env variable TEXT_GENERATION_CACHE_DIR, if it is not set
# we use a default cache directory at <install_path>/api/.cache
# (None by default)
cache_dir=None,
# optional path to a download directory where pretrained models will be downloaded to,
# if None, we check the env variable TEXT_GENERATION_DOWNLOAD_DIR, if it is not set
# we use a default download directory at <install_path>/api/.download
# (None by default)
download_dir=None,
# force download of model even if it already exists in download dir
# (False by default)
force_download=False
)
```
When used for the first time with the command line interface or Python API the pretrained model will be automatically downloaded.
However, you can also download our pretrained models first as zip files, put them in a directory on your local drive
and set `TEXT_GENERATION_DOWNLOAD_DIR` (or the `download_dir` parameter above) to this directory.
#### Use own model
Once you trained your own model you can use it in the following way.
```python
from llm_text_generation import TextGenerator
gen = TextGenerator.from_experiment(
# path to the experiment directory that is created by your training run
experiment_dir="path/to/experiment_dir",
# the device to run the model on
# ("cuda" by default)
device="cuda"
)
```
### Directory structure
The most important directories you might want to look at are:
```
configs -> (example yaml config files for training and server)
src -> (library code used by this project)
```
### Docker
You can also run this project using docker. Build the image using
`docker build -t llm-text-generation .`
If you have an older GPU build the image using
`docker build -t llm-text-generation -f Dockerfile.old .`
By default, the entrypoint is set to the `llm-gen` command,
so you can use the Docker setup like described [here](#from-command-line) earlier.
You can mount /llm-gen/cache and /llm-gen/download to volumes on your machine, such that
you do not need to download the models every time.
```bash
# complete text
docker run llm-text-generation -p "completethisplease"
# complete file
docker run llm-text-generation -f path/to/file.txt
# start a server
docker run llm-text-generation --server path/to/config.yaml
# with volumes
docker run -v $(pwd)/.cache:/llm-gen/cache -v $(pwd)/.download:/llm-gen/download \
llm-text-generation -c "completethisplease"
# optional parameters recommended when using a GPU:
# --gpus all --ipc=host --ulimit memlock=-1 --ulimit stack=67108864
Note
----
Make sure you have docker version >= 19.03, a nvidia driver
and the nvidia container toolkit installed (see https://github.com/NVIDIA/nvidia-docker)
if you want to run the container with GPU support.
```
Raw data
{
"_id": null,
"home_page": null,
"name": "llm-text-generation",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.10",
"maintainer_email": null,
"keywords": "nlp, text, llm",
"author": null,
"author_email": "Sebastian Walter <swalter@cs.uni-freiburg.de>",
"download_url": null,
"platform": null,
"description": "## LLM Text Generation\n\nGenerate natural language text with large language models.\n\n### Installation\n\nThis project requires Python 3.10 or higher.\n\n#### From PyPI\n\n```bash\npip install llm-text-generation\n```\n\n#### From source\n\n```bash\ngit clone git@github.com:ad-freiburg/llm-text-generation.git\ncd llm-text-generation\npip install -e .\n\n```\n\n### Usage\n\n#### From Python\n\n#### From command line\n\nAfter installation the command `llm-gen` is available in your python environment. \nIt lets you use the text generation models directly from the command line.\nBelow are examples of how to use `llm-gen`. See `llm-gen -h` for all options.\n\n```bash\n# print version\nllm-gen -v\n\n# list available models\nllm-gen -l\n\n# by default llm-gen tries to read stdin, complete the input it got line by line \n# and prints the completed lines back out\n# therefore, you can for example use text generation with pipes\necho \"The capital of Germany is\" | llm-gen\ncat \"path/to/input/file.txt\" | llm-gen > output.txt\n\n# complete a string using\nllm-gen -p \"The capital of Germany is\"\n\n# complete a text file line by line and print the completed lines\nllm-gen -f path/to/input/file.txt\n# optionally specify an output file path where the completed lines are saved\nllm-gen -f path/to/input/file.txt -o output.txt\n\n# start an interactive text generation session\n# where your input will be completeed and printed back out\nllm-gen -i\n\n# start a text generation server with the following endpoints:\n### /models [GET] --> output: available models as json \n### /info [GET] --> output: info about backend as json\n### /generate [POST] input: some input text --> output: continuation of the input text\n### /live [WS] websocket endpoint for live text generation (only single unbatched requests)\nllm-gen --server <config_file>\n\n### OPTIONS\n### Pass the following flags to the llm-gen command to customize its behaviour\n-m <model_name> # use a different text generation model than the default one \n--cpu # force execution on CPU, by default a GPU is used if available\n--progress # display a progress bar (always on when a file is repaired using -f)\n-b <batch_size> # specify a different batch size\n-batch-max-tokens <batch_max_tokens> # limit batch by a number of tokens and not by number of samples\n-u # do not sort the inputs before completeing\n-e <experiment_dir> # specify the path to an experiment directory to load the model from \n # (equivalent to TextGenerator.from_experiment(experiment_dir) in Python API)\n--force-download # force download of the text generation model even if it was already downloaded\n--progress # show a progress bar while completing\n--report # print a report on the runtime of the model after finishing the completion\n```\n\n> Note: When first using `llm-gen` with a pretrained model, the model needs to be downloaded, so depending on\n> your internet speed the command might take considerably longer.\n\n> Note: Loading the text generation model requires an initial startup time each time you\n> invoke the `llm-gen` command. CPU startup time is around 1s, GPU startup time around 3.5s, so for small\n> inputs or files you should probably pass the `--cpu` flag to force CPU execution for best performance.\n\n> See [configs/server.yaml](configs/server.yaml) for an exemplary server configuration file.\n\n### Documentation\n\n#### Use pretrained model\n\nIf you just want to use this project to complete whitespaces, this is the recommended way.\n\n```python\nfrom llm_text_generation import TextGenerator\n\ngen = TextGenerator.from_pretrained(\n # pretrained model to load, get all available models from available_models(),\n # if None, loads the default model\n model=None,\n # the device to run the model on\n # (\"cuda\" by default)\n device=\"cuda\",\n # optional path to a cache directory where downloaded models will be extracted to,\n # if None, we check the env variable TEXT_GENERATION_CACHE_DIR, if it is not set \n # we use a default cache directory at <install_path>/api/.cache \n # (None by default)\n cache_dir=None,\n # optional path to a download directory where pretrained models will be downloaded to,\n # if None, we check the env variable TEXT_GENERATION_DOWNLOAD_DIR, if it is not set \n # we use a default download directory at <install_path>/api/.download\n # (None by default)\n download_dir=None,\n # force download of model even if it already exists in download dir\n # (False by default)\n force_download=False\n)\n```\n\nWhen used for the first time with the command line interface or Python API the pretrained model will be automatically downloaded. \nHowever, you can also download our pretrained models first as zip files, put them in a directory on your local drive \nand set `TEXT_GENERATION_DOWNLOAD_DIR` (or the `download_dir` parameter above) to this directory.\n\n#### Use own model\n\nOnce you trained your own model you can use it in the following way.\n\n```python\nfrom llm_text_generation import TextGenerator\n\ngen = TextGenerator.from_experiment(\n # path to the experiment directory that is created by your training run\n experiment_dir=\"path/to/experiment_dir\",\n # the device to run the model on\n # (\"cuda\" by default)\n device=\"cuda\"\n)\n```\n\n### Directory structure\n\nThe most important directories you might want to look at are:\n\n```\nconfigs -> (example yaml config files for training and server)\nsrc -> (library code used by this project)\n```\n\n### Docker\n\nYou can also run this project using docker. Build the image using\n\n`docker build -t llm-text-generation .`\n\nIf you have an older GPU build the image using\n\n`docker build -t llm-text-generation -f Dockerfile.old .`\n\nBy default, the entrypoint is set to the `llm-gen` command, \nso you can use the Docker setup like described [here](#from-command-line) earlier.\n\nYou can mount /llm-gen/cache and /llm-gen/download to volumes on your machine, such that\nyou do not need to download the models every time.\n\n```bash\n# complete text\ndocker run llm-text-generation -p \"completethisplease\"\n\n# complete file\ndocker run llm-text-generation -f path/to/file.txt\n\n# start a server\ndocker run llm-text-generation --server path/to/config.yaml\n\n# with volumes\ndocker run -v $(pwd)/.cache:/llm-gen/cache -v $(pwd)/.download:/llm-gen/download \\\n llm-text-generation -c \"completethisplease\"\n\n# optional parameters recommended when using a GPU:\n# --gpus all --ipc=host --ulimit memlock=-1 --ulimit stack=67108864\n\nNote\n----\nMake sure you have docker version >= 19.03, a nvidia driver\nand the nvidia container toolkit installed (see https://github.com/NVIDIA/nvidia-docker)\nif you want to run the container with GPU support.\n```\n",
"bugtrack_url": null,
"license": "Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. \"License\" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. \"Licensor\" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. \"Legal Entity\" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, \"control\" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. \"You\" (or \"Your\") shall mean an individual or Legal Entity exercising permissions granted by this License. \"Source\" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. \"Object\" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types. \"Work\" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below). \"Derivative Works\" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof. \"Contribution\" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, \"submitted\" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Work, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as \"Not a Contribution.\" \"Contributor\" shall mean Licensor and any individual or Legal Entity on behalf of whom a Contribution has been received by Licensor and subsequently incorporated within the Work. 2. Grant of Copyright License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. 3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed. 4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and (b) You must cause any modified files to carry prominent notices stating that You changed the files; and (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and (d) If the Work includes a \"NOTICE\" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License. You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. 5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions. 6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file. 7. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. 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