Text Generation
QuantumPeer
OpenPeerLLM
PyTorch
English
quantum-llm
quantum-computing
chern-simons
neural-networks
causal-lm
decentralized-learning
transformer
boinc
decent-torch
lonscript
Eval Results (legacy)
Instructions to use OpenPeerAI/QuantumPeer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- QuantumPeer
How to use OpenPeerAI/QuantumPeer with QuantumPeer:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- OpenPeerLLM
How to use OpenPeerAI/QuantumPeer with OpenPeerLLM:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 547 Bytes
a49d7b4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | from setuptools import setup, find_packages
with open("README.md", "r", encoding="utf-8") as fh:
long_description = fh.read()
setup(
name="quantumpeer",
version="0.1.0",
author="[Andrew Magdy Kamal Nassief]",
packages=find_packages(where="src"),
package_dir={"": "src"},
python_requires=">=3.8",
install_requires=[
"numpy>=1.20.0",
"scipy>=1.7.0",
],
extras_require={
"dev": [
"pytest>=7.0.0",
"pytest-cov>=2.12.0",
],
},
) |