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: 453 Bytes
21a9138 | 1 2 3 4 5 6 7 8 9 10 | """Layer 1 of the first line of defense: reduce code to what it does (behaviours with locations and operands).
Descriptive only. Behaviour presence is not a verdict; layer 2 judges behaviours against the task and the
repository's normal behaviour. Analysed code is never executed.
"""
from .engine import analyse_diff, analyse_package, analyse_snippet # noqa: F401
from .model import KINDS, KIND_HELP, render_text # noqa: F401
__version__ = "0.1.0"
|