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
Download extractor/behaviour/tests/__init__.py from stonefish-labs/d3-mini-agentcode: direct link, hf CLI and curl.
- Browser
- Download file 413 Bytes
-
https://huggingface.co/stonefish-labs/d3-mini-agentcode/resolve/main/extractor/behaviour/tests/__init__.py
- Command line
-
hf download hf://stonefish-labs/d3-mini-agentcode/extractor/behaviour/tests/__init__.py
-
curl -L -o __init__.py https://huggingface.co/stonefish-labs/d3-mini-agentcode/resolve/main/extractor/behaviour/tests/__init__.py
413 Bytes
| """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 | |