Text Generation
GGUF
English
Arabic
code
gemma2
google
mantiq
logic
arabic
epistemology
reasoning
chain-of-thought
aynengine
conversational
Instructions to use enver/ayncoding-gemma2-2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use enver/ayncoding-gemma2-2b with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf enver/ayncoding-gemma2-2b # Run inference directly in the terminal: llama cli -hf enver/ayncoding-gemma2-2b
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf enver/ayncoding-gemma2-2b # Run inference directly in the terminal: llama cli -hf enver/ayncoding-gemma2-2b
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf enver/ayncoding-gemma2-2b # Run inference directly in the terminal: ./llama-cli -hf enver/ayncoding-gemma2-2b
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf enver/ayncoding-gemma2-2b # Run inference directly in the terminal: ./build/bin/llama-cli -hf enver/ayncoding-gemma2-2b
Use Docker
docker model run hf.co/enver/ayncoding-gemma2-2b
- Llama new
- LM Studio
- Jan
- vLLM
How to use enver/ayncoding-gemma2-2b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "enver/ayncoding-gemma2-2b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "enver/ayncoding-gemma2-2b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/enver/ayncoding-gemma2-2b
- Ollama
How to use enver/ayncoding-gemma2-2b with Ollama:
ollama run hf.co/enver/ayncoding-gemma2-2b
- Unsloth Desktop
- Docker Model Runner
How to use enver/ayncoding-gemma2-2b with Docker Model Runner:
docker model run hf.co/enver/ayncoding-gemma2-2b
- Lemonade
How to use enver/ayncoding-gemma2-2b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull enver/ayncoding-gemma2-2b
Run and chat with the model
lemonade run user.ayncoding-gemma2-2b-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
File size: 7,227 Bytes
083c80f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 | #!/usr/bin/env python3
"""
classical_text_miner.py
AynEngine AI Coding Edition: Classical Text & Lexicon Miner.
Directly mines passages, definitions, and logical axioms from the classical corpus:
- Abū Ḥāmid al-Ghazālī: Miʿyār al-ʿIlm fī Fann al-Manṭiq & Miḥakk al-Naẓar
- Al-Farāhīdī: Kitāb al-ʿAyn
- Al-Rāghib al-Iṣfahānī: Al-Mufradāt fī Gharīb al-Qurʾān
- Al-Zamakhsharī: Asās al-Balāghah
- Ibn Manẓūr: Lisān al-ʿArab
- Sībawayh: Al-Kitāb
"""
import json
import re
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, List, Any, Optional
@dataclass
class ClassicalAxiom:
"""An authentic logical or morphological rule extracted from the classical books."""
source_author: str # e.g., 'Abū Ḥāmid al-Ghazālī'
book_title: str # e.g., 'Miʿyār al-ʿIlm'
topic_category: str # e.g., 'Dafʿ al-Dawr', 'Taṣawwur vs Taṣdīq'
arabic_passage: str # Excerpted Arabic text
epistemic_rule: str # The derived software engineering invariant
class ClassicalTextMiner:
"""Mines and indexes definitions and proof rules from local Arabic classical texts."""
DEFAULT_DATA_DIR = Path("/home/absolut7/.gemini/antigravity/scratch/translation_engine_framework/data")
def __init__(self, data_dir: Optional[Path] = None):
self.data_dir = data_dir or self.DEFAULT_DATA_DIR
self.texts_dir = self.data_dir / "texts"
self.lexicons_dir = self.data_dir / "lexicons"
self.grammars_dir = self.data_dir / "grammars"
# File paths
self.miyar_file = self.texts_dir / "ghazali/miyar_al_ilm.txt"
self.mihakk_file = self.texts_dir / "ghazali/mihakk_al_nazar.txt"
self.mufradat_file = self.texts_dir / "raghib/al_mufradat_fi_gharib_al_quran.txt"
self.asas_json = self.lexicons_dir / "zamakhshari_asas/asas_balagha_dictionary.json"
self.kitab_ayn_json = self.lexicons_dir / "kitab_al_ayn/kitab_al_ayn_dictionary.json"
self.lisan_json = self.data_dir / "lisanclean.json"
self.sibawayh_json = self.grammars_dir / "sibawayh_rules.json"
self._cached_asas: Optional[Dict[str, Any]] = None
self._cached_ayn: Optional[Dict[str, Any]] = None
self._cached_lisan: Optional[Dict[str, Any]] = None
self._cached_sibawayh: Optional[Dict[str, Any]] = None
def search_mantiq_passages(self, keyword: str, max_results: int = 3) -> List[ClassicalAxiom]:
"""Searches Miʿyār al-ʿIlm and Miḥakk al-Naẓar for passages matching a logical keyword."""
results: List[ClassicalAxiom] = []
files_to_scan = [
(self.miyar_file, "Abū Ḥāmid al-Ghazālī", "Miʿyār al-ʿIlm"),
(self.mihakk_file, "Abū Ḥāmid al-Ghazālī", "Miḥakk al-Naẓar")
]
for filepath, author, book in files_to_scan:
if not filepath.exists():
continue
text = filepath.read_text(encoding="utf-8", errors="ignore")
# Split into semantic paragraphs
paragraphs = [p.strip() for p in text.split("\n\n") if len(p.strip()) > 60]
for p in paragraphs:
if keyword in p:
# Clean up paragraph
cleaned_p = re.sub(r"\s+", " ", p)
axiom = ClassicalAxiom(
source_author=author,
book_title=book,
topic_category=f"Logical Analysis: {keyword}",
arabic_passage=cleaned_p[:350] + ("..." if len(cleaned_p) > 350 else ""),
epistemic_rule=self._derive_rule_from_keyword(keyword)
)
results.append(axiom)
if len(results) >= max_results:
return results
return results
def _derive_rule_from_keyword(self, kw: str) -> str:
"""Derives the software engineering constraint from the classical logical keyword."""
rules = {
"الدور": "Dafʿ al-Dawr: Mutual/circular dependency is an epistemic impossibility. Every component must be hierarchically governed.",
"التسلسل": "Dafʿ al-Tasalsul: Unbounded regress causes system failure. Every recursive, retry, or looping routine must have a strictly bounded termination proof.",
"الحد": "Al-Ḥadd al-Tāmm: Essential specification requires Genus and Specific Difference (Jins + Faṣl). Never expose unconstrained generic wrappers.",
"التناقض": "ʿAdam al-Tanāquḍ: Contradictory states cannot co-exist in true reality. Make illegal states unrepresentable in the type system.",
"التصور": "Taṣawwur precedes Taṣdīq: Indivisible domain types must be formulated before implementing runtime mutations.",
"البرهان": "Al-Burhān: Demonstrative proof required. Code must compile without warnings, with verified types and complete error coverage."
}
return rules.get(kw, "Epistemic invariant derived from classical Ghazalian logic.")
def lookup_root_definition(self, root_str: str) -> Dict[str, str]:
"""
Looks up a tri-consonantal root across Kitāb al-ʿAyn, Lisān al-ʿArab, and Asās al-Balāghah.
Returns definitions and Haqiqah vs Majaz distinctions.
"""
lookup_result: Dict[str, str] = {
"root": root_str,
"kitab_al_ayn": "",
"asas_balagha": "",
"lisan_al_arab": ""
}
# 1. Asās al-Balāghah (Zamakhshari)
if self._cached_asas is None and self.asas_json.exists():
try:
self._cached_asas = json.loads(self.asas_json.read_text(encoding="utf-8"))
except Exception:
self._cached_asas = {}
if self._cached_asas and root_str in self._cached_asas:
entry = self._cached_asas[root_str]
lookup_result["asas_balagha"] = str(entry)[:300]
# 2. Kitāb al-ʿAyn (Farahidi)
if self._cached_ayn is None and self.kitab_ayn_json.exists():
try:
self._cached_ayn = json.loads(self.kitab_ayn_json.read_text(encoding="utf-8"))
except Exception:
self._cached_ayn = {}
if self._cached_ayn:
# Check with and without spaces
spaced_root = " ".join(list(root_str))
if spaced_root in self._cached_ayn:
lookup_result["kitab_al_ayn"] = str(self._cached_ayn[spaced_root])[:300]
elif root_str in self._cached_ayn:
lookup_result["kitab_al_ayn"] = str(self._cached_ayn[root_str])[:300]
return lookup_result
def extract_core_mantiq_canon(self) -> List[ClassicalAxiom]:
"""Pulls the primary canon of Manṭiq axioms for dataset construction."""
canon: List[ClassicalAxiom] = []
keywords = ["الحد", "الدور", "التسلسل", "التناقض", "التصور", "البرهان"]
for kw in keywords:
passages = self.search_mantiq_passages(kw, max_results=1)
canon.extend(passages)
return canon
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