Foundation Model Inferencing
Setting up Pre-commit for this Repository
Pre-commit helps to manage and maintain code quality by running hooks that perform various checks before a commit is made.
To set up pre-commit for this repository, follow these steps:
-
Install pre-commit. If you're using pip, you can do this by running:
pip install pre-commit -
Navigate to the root directory of the repository where the .pre-commit-config.yaml file is located.
-
Run the following command to install the git hook scripts:
pre-commit install
Now, pre-commit will run automatically on git commit. If you want to manually run all pre-commit hooks on a repository, run:
pre-commit run --all-files
To run a specific pre-commit hook on all files, you can use the run command followed by the ID of the hook. Here's the general syntax:
pre-commit run <hook_id> --all-files
For example, if you want to run the black hook on all files, you would use:
pre-commit run black --all-files
This command will run the black hook on every file in your repository.
Hooks Used in this Repository
This repository uses a variety of hooks to maintain code quality:
- check-added-large-files: Prevents committing large files.
- end-of-file-fixer: Ensures files end with a newline.
- trailing-whitespace: Removes trailing whitespace.
- check-ast: Checks Python AST for syntax errors.
- check-docstring-first: Ensures the first thing in a Python file is a docstring.
- isort: Sorts Python imports.
- add-trailing-comma: Adds trailing commas to Python data structures.
- black: Formats Python code to conform to the PEP 8 style guide.
- flake8: Lints Python code for errors and code style violations.
- pydocstyle: Checks Python docstring conventions.
These hooks are run automatically before each commit once pre-commit is installed.
Metadata
Release files for llm-optimized-inference 0.2.61
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| llm_optimized_inference-0.2.61-py3-none-any.whl | Python 3 | none | any | Details for llm_optimized_inference-0.2.61-py3-none-any.whl |
Release files / llm_optimized_inference-0.2.61-py3-none-any.whl
| Download URL | llm_optimized_inference-0.2.61-py3-none-any.whl |
|---|---|
| Size | 88.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
f7bd7c71ac06af298c85135e276c9d5b0b326776ddbe16314e4cf7699fcef12d
|
|
BLAKE2b-256 checksum How to use checksums |
17aecbbdf389a219f3dafaf5398a97716ca10ce8a453ff5b85967fb227d5c503
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.12.10
|
Security for llm-optimized-inference 0.2.61
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.