Zero-Shot Classification
Transformers
Safetensors
qwen3_5
feature-extraction
security
code-review
ai-agents
decision-model
d3
system-one
pre-release
custom_code
Instructions to use stonefish-labs/d3-mini-agentcode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stonefish-labs/d3-mini-agentcode with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="stonefish-labs/d3-mini-agentcode", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("stonefish-labs/d3-mini-agentcode", trust_remote_code=True) model = AutoModel.from_pretrained("stonefish-labs/d3-mini-agentcode", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 413 Bytes
21a9138 | 1 2 3 4 5 6 7 8 9 10 11 | """Test package; `python -m unittest behaviour.tests` loads every test_*.py here."""
import unittest
from pathlib import Path
def load_tests(loader, standard_tests, pattern):
here = Path(__file__).parent
standard_tests.addTests(loader.discover(start_dir=str(here), pattern=pattern or "test*.py",
top_level_dir=str(here.parents[1])))
return standard_tests
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