d1-2B

pip install "transformers>=5.19" torch torchvision pillow

import torch
from transformers import AutoModel

device = "cuda" if torch.cuda.is_available() else "mps" if torch.backends.mps.is_available() else "cpu"
dtype = torch.float32 if device == "cpu" else torch.bfloat16
model = AutoModel.from_pretrained("LiquidAI/d1-2B", trust_remote_code=True, dtype=dtype).to(device)

questions = {
    "refund": {"type": "noul", "instructions": "Is the customer asking for a refund?"},
    "team": {"type": "choice", "instructions": "Which team should handle this?",
             "criteria": {"billing": "Charges, refunds, invoices", "shipping": "Delivery and parcels",
                          "technical": "App or site faults"}},
    "topics": {"type": "choice", "multiple": True, "instructions": "Which topics does the message raise?",
               "criteria": {"billing": "Payments and charges", "delivery": "Shipping and parcels",
                            "login": "Signing in to the account"}},
    "urgency": {"type": "score", "instructions": "How urgent is this ticket?", "criteria": ["low", "medium", "high"]},
}
output = model.system_one("I was charged twice and my parcel never arrived. Please refund one charge.", questions)
a = output["answers"]
urgency = a["urgency"]["legend"][str(int(a["urgency"]["score"]))]
print(round(a["refund"]["noul"], 2), a["team"]["choice"], a["topics"]["choices"], urgency)
# 1.0 billing ['billing', 'delivery'] medium

invoice = "ACME SA\nInvoice 2026-117\nTotal due: 1 234,50 EUR\nPay before 03/04/2026 (day/month/year)"
output = model.system_one(invoice, {
    "payee": {"type": "text", "instructions": "Who issued the invoice?"},
    "total": {"type": "number", "instructions": "How much is due?"},
    "due": {"type": "date", "instructions": "By when must it be paid?"},
    "vat": {"type": "number", "instructions": "How much VAT is charged?"},
})
a = output["answers"]
print(a["payee"]["text"], a["total"]["number"], a["due"]["date"], a["vat"]["number"])
# ACME SA 1234.5 2026-04-03 None

from transformers.image_utils import load_image

image = load_image("http://images.cocodataset.org/val2017/000000039769.jpg")
output = model.system_one(None, {
    "cats": {"type": "number", "instructions": "How many cats are there?", "range": [0, 10], "step": 1},
    "remote": {"type": "box", "instructions": "Where is the remote control on the left?"},
    "every_cat": {"type": "boxes", "instructions": "Every cat.", "max": 4},
}, media=[image])
a = output["answers"]
print(a["cats"]["number"], a["every_cat"]["count"], {k: round(v, 2) for k, v in a["remote"]["box"].items()})
# 2.0 2 {'top': 0.15, 'bottom': 0.24, 'left': 0.06, 'right': 0.28}

tickets = ["Where is my parcel? It was due Monday.", "The app crashes when I open settings."]
for output in model.system_one_batch([(t, {"team": questions["team"]}) for t in tickets]):
    print(output["answers"]["team"]["choice"])
# shipping
# technical