Text Generation
OpenPeerLLM
Safetensors
PyTorch
English
causal-lm
decentralized-learning
transformer
boinc
decent-torch
lonscript
Eval Results (legacy)
Instructions to use OpenPeerAI/OpenPeerLLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenPeerLLM
How to use OpenPeerAI/OpenPeerLLM 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
| # LonScript Grammar Parser | |
| from typing import List, Dict | |
| class LonScriptGrammar: | |
| def __init__(self): | |
| self.rules = { | |
| 'FUNCTION': r'fn\s+([a-zA-Z_][a-zA-Z0-9_]*)\s*\((.*?)\)', | |
| 'VARIABLE': r'let\s+([a-zA-Z_][a-zA-Z0-9_]*)\s*=\s*(.*)', | |
| 'CONDITIONAL': r'if\s+(.*?)\s*then', | |
| 'LOOP': r'loop\s+(.*?)\s*do', | |
| 'PROCESS': r'process\s+(.*?)\s*with', | |
| } | |
| def parse_text(self, text: str) -> Dict: | |
| """Parse text using LonScript grammar rules""" | |
| parsed_elements = { | |
| 'functions': [], | |
| 'variables': [], | |
| 'conditionals': [], | |
| 'loops': [], | |
| 'processes': [] | |
| } | |
| # Implementation of grammar parsing logic here | |
| return parsed_elements | |
| def apply_grammar_rules(self, text: str) -> str: | |
| """Apply LonScript grammar rules to enhance text understanding""" | |
| parsed = self.parse_text(text) | |
| # Transform text based on parsed elements | |
| return self._transform_text(text, parsed) | |
| def _transform_text(self, text: str, parsed_elements: Dict) -> str: | |
| """Transform text based on parsed grammar elements""" | |
| # Implementation of text transformation logic | |
| return text |