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: 985 Bytes
21a9138 | 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 | {
"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"
}
} |