semvec/pypi-packages huggingface dataset:
ucdp-amba 0.9.2
Unified Chip Design Platform - AMBA
Requires Python: <4.0,>=3.10.0

[![PyPI Version](https://badge.fury.io/py/ucdp-amba.svg)](https://badge.fury.io/py/ucdp-amba)
[![Python Build](https://github.com/nbiotcloud/ucdp-amba/actions/workflows/main.yml/badge.svg)](https://github.com/nbiotcloud/ucdp-amba/actions/workflows/main.yml)
[![Documentation](https://readthedocs.org/projects/ucdp-amba/badge/?version=stable)](https://ucdp-amba.readthedocs.io/en/stable/?badge=stable)
[![Coverage Status](https://coveralls.io/repos/github/nbiotcloud/ucdp-amba/badge.svg?branch=main)](https://coveralls.io/github/nbiotcloud/ucdp-amba?branch=main)
[![python-versions](https://img.shields.io/pypi/pyversions/ucdp-amba.svg)](https://pypi.python.org/pypi/ucdp-amba)

# Unified Chip Design Platform - AMBA

* [Documentation](https://ucdp-amba.readthedocs.io/en/stable/)
* [PyPI](https://pypi.org/project/ucdp-amba/)
* [Sources](https://github.com/nbiotcloud/ucdp-amba)
* [Issues](https://github.com/nbiotcloud/ucdp-amba/issues)

## Installation

Installing it is pretty easy:

```bash
pip install ucdp-amba
```
specpipe 0.3.7
Deprecated: this project has been renamed to swectral.
Requires Python: >=3.9
Keywords: hyperspectral-imaging, spectral-image-processing, hyperspectral-modeling, model-evaluation-automation, spectral-modeling-pipeline

# SpecPipe (DEPRECATED)

**This project has been renamed to `swectral`.**

`specpipe` is no longer maintained. All development, support, and future releases continue under the new package name, `swectral`.

## Install the new package

```bash
pip install swectral
```

The replacement package is available at:

- PyPI: https://pypi.org/project/swectral/
- GitHub: https://github.com/siwei66/swectral
aeclib 0.0.1
Open-source computational logic engine for global building codes and standards.
Requires Python: >=3.9

# aeclib
Open-source computational logic for global building codes and standards.

aeclib translates building code provisions into executable and testable logic.

## Project Status: Pre-Alpha
This package is currently in the foundation phase. We are securing the namespace and establishing the core architecture.

## Intent
The goal of aeclib is to provide a unified "Logic Layer" for the AEC industry to support automated compliance and computational design.

## License
Licensed under the Apache License 2.0.
powerpax 0.2.1
Small collection of useful utilities for JAX
Requires Python: >=3.10

# Powerpax: Utilities for JAX

[![Powerpax on PyPI](https://img.shields.io/pypi/v/powerpax)][pypi]
[![Powerpax on conda-forge](https://img.shields.io/conda/vn/conda-forge/powerpax.svg)][condaforge]
[![Documentation](https://readthedocs.org/projects/powerpax/badge/?version=latest)][docs]
[![Tests](https://github.com/karlotness/powerpax/actions/workflows/test.yml/badge.svg)][tests]

A collection of utility functions for JAX.

- **Documentation** https://powerpax.readthedocs.io/en/latest/
- **Source Code:** https://github.com/karlotness/powerpax
- **Bug Reports:** https://github.com/karlotness/powerpax/issues

## Installation
Install from [PyPI][pypi] using pip:
```console
$ python -m pip install powerpax
```
or from [conda-forge][condaforge]:
``` console
$ conda install -c conda-forge powerpax
```

This should install required dependencies, but JAX itself may require
special attention, particularly for GPU support.
Follow the [JAX installation instructions](https://jax.readthedocs.io/en/latest/installation.html).

## License
This software is distributed under the MIT license. See LICENSE.txt
for the license text.

[pypi]: https://pypi.org/project/powerpax/
[condaforge]: https://anaconda.org/conda-forge/powerpax
[docs]: https://powerpax.readthedocs.io/en/latest/
[tests]: https://github.com/karlotness/powerpax/actions/workflows/test.yml
dunebench 0.4
dunebench – a lightweight evaluation tool for llama.cpp models
Requires Python: >=3.8


# DuneBench

**dunebench** is a lightweight, local benchmarking tool for GGUF models. It allows you to evaluate Large Language Models (LLMs) across a variety of domains—including logic, coding, math, and common sense—using `llama-cpp-python`.


![Logo](https://i.postimg.cc/SN3h7cYQ/dunebench-(1).png)


# Installation

Install dunebench with `pip`

```bash
    pip install dunebench
```
or install EXE with this [link](https://mega.nz/file/y7AFAASS#nfrjiWcEYG60AggSuhkHlvoakKHl6ZKreAnlFINXC1U)

# Features

* **Local Evaluation:** Runs entirely on your machine using GGUF models.
* **GPU Accelerated:** Offload layers to your GPU for faster testing.
* **Multi-Domain Support:** Includes 8 distinct benchmarks (Math, Coding, Science, etc.).

# Usage/Examples

```bash
python -m dunebench --model "path/to/model.gguf" --task science --limit 20
```
### Arguments
| Argument | Description                          | Default  |
|----------|--------------------------------------|----------|
| `--model` | Path to your `.gguf` model file       | Required |
| `--task`  | The benchmark task to run             | Required |
| `--limit` | Number of samples to test             | `10`     |

### Tasks

| Task Name        | Dataset Used           | Domain                   | Type              |
|------------------|------------------------|--------------------------|-------------------|
| science          | ai2_arc (Challenge)    | Scientific Reasoning     | Multiple Choice   |
| math             | gsm8k                  | Math Word Problems       | Generation        |
| programming      | mbpp (Sanitized)       | Python Coding            | Code Generation   |
| physical_logic   | piqa                   | Physical Commonsense     | Multiple Choice   |
| common_sense     | openbookqa             | General Knowledge        | Multiple Choice   |
| logic            | winogrande             | Ambiguity Resolution     | Multiple Choice   |
| grammar          | glue (CoLA)            | Linguistic Acceptability | Multiple Choice   |
| nlp              | hellaswag              | Sentence Completion      | Multiple Choice   |

# License

[MIT](https://choosealicense.com/licenses/mit/)


# Authors

- [@Rudransh Joshi](https://rudransh.kafalfpc.com/)