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 adapter/training_args.json from stonefish-labs/d3-mini-agentcode: direct link, hf CLI and curl.
- Browser
- Download file 985 Bytes
-
https://huggingface.co/stonefish-labs/d3-mini-agentcode/resolve/main/adapter/training_args.json
- Command line
-
hf download hf://stonefish-labs/d3-mini-agentcode/adapter/training_args.json
-
curl -L -o training_args.json https://huggingface.co/stonefish-labs/d3-mini-agentcode/resolve/main/adapter/training_args.json
985 Bytes
| { | |
| "base": "vllm-sr/d3-mini@df99bf4ca4418bc6908ee68e9b7479af1f3b8800", | |
| "seed": 1, | |
| "optimizer_steps": 1038, | |
| "selected_checkpoint": "final", | |
| "args": { | |
| "dtype": "bfloat16", | |
| "max_length": "8192", | |
| "max_tokens": "8192", | |
| "grad_accum": "16", | |
| "epochs": "2.0", | |
| "max_steps": "0", | |
| "lr": "0.0001", | |
| "readout_lr": "2e-05", | |
| "weight_decay": "0.0", | |
| "warmup": "0.05", | |
| "clip": "1.0", | |
| "lora_r": "16", | |
| "lora_alpha": "32", | |
| "lora_dropout": "0.05", | |
| "lora_targets": "['q_proj', 'k_proj', 'v_proj', 'o_proj', 'in_proj_qkv', 'in_proj_z', 'out_proj', 'gate_proj', 'up_proj', 'down_proj']", | |
| "rslora": "False", | |
| "freeze_readout": "False", | |
| "label_smoothing": "0.05", | |
| "shuffle_choices": "True", | |
| "no_grad_ckpt": "False", | |
| "eval_every": "400", | |
| "save_every": "400", | |
| "eval_batch": "8", | |
| "seed": "1", | |
| "log_every": "10", | |
| "vram_margin_gib": "3.0", | |
| "no_vram_check": "False", | |
| "abort_on_low_vram": "True" | |
| } | |
| } |