Instructions to use litert-community/d1-2B-LiteRT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use litert-community/d1-2B-LiteRT with LiteRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
d1-2B for LiteRT: decision graphs at seven lengths, the eight-sequence and eight-signature files, seven picture towers, five SM8850 NPU files, the PyTorch-free host, the fixtures and the conversion scripts
df44977 verified Download examples/run_example.expected.json from litert-community/d1-2B-LiteRT: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/litert-community/d1-2B-LiteRT/resolve/main/examples/run_example.expected.json
- Command line
-
hf download hf://litert-community/d1-2B-LiteRT/examples/run_example.expected.json
-
curl -L -o run_example.expected.json https://huggingface.co/litert-community/d1-2B-LiteRT/resolve/main/examples/run_example.expected.json
4.03 kB
| { | |
| "what": "the answers of the provider's own code (LiquidAI/d1-2B at revision 10e7671d44e4b37700020b1eed3f594c5f2af0b4, transformers 5.19.0, torch 2.14.1) in float32 on the CPU, one request per call, to the model card's examples as examples/run_example.py sends them", | |
| "tolerance": { | |
| "probability": 0.0001, | |
| "box_edge": 0.002, | |
| "box_confidence": 0.02, | |
| "other": "equal" | |
| }, | |
| "examples": { | |
| "ticket": { | |
| "answers": { | |
| "refund": { | |
| "type": "noul", | |
| "noul": 0.9969030435870195 | |
| }, | |
| "team": { | |
| "type": "choice", | |
| "choice": "billing", | |
| "confidence": 0.7103015575840597, | |
| "probabilities": { | |
| "billing": 0.7103015575840597, | |
| "shipping": 0.24445433912175446, | |
| "technical": 0.04524410329418587 | |
| } | |
| }, | |
| "topics": { | |
| "type": "choice", | |
| "choices": [ | |
| "billing", | |
| "delivery" | |
| ], | |
| "probabilities": { | |
| "billing": 0.943041315622141, | |
| "delivery": 0.9678893962329417, | |
| "login": 0.0 | |
| } | |
| }, | |
| "urgency": { | |
| "type": "score", | |
| "score": 1.0, | |
| "confidence": 0.6731814240252898, | |
| "probabilities": { | |
| "0": 0.2340110456452715, | |
| "1": 0.6731814240252898, | |
| "2": 0.09280753032943866 | |
| }, | |
| "legend": { | |
| "0": "low", | |
| "1": "medium", | |
| "2": "high" | |
| } | |
| } | |
| }, | |
| "usage": { | |
| "input_tokens": 189, | |
| "output_tokens": 0 | |
| } | |
| }, | |
| "invoice": { | |
| "answers": { | |
| "payee": { | |
| "type": "text", | |
| "text": "ACME SA", | |
| "span": [ | |
| 0, | |
| 7 | |
| ], | |
| "found": 0.9973788775950928 | |
| }, | |
| "total": { | |
| "type": "number", | |
| "number": 1234.5, | |
| "span": [ | |
| 36, | |
| 48 | |
| ], | |
| "found": 1.0, | |
| "text": "1 234,50 EUR", | |
| "unit": "EUR" | |
| }, | |
| "due": { | |
| "type": "date", | |
| "date": "2026-04-03", | |
| "span": [ | |
| 60, | |
| 70 | |
| ], | |
| "found": 1.0, | |
| "text": "03/04/2026" | |
| }, | |
| "vat": { | |
| "type": "number", | |
| "number": null, | |
| "span": null, | |
| "found": 0.0, | |
| "text": null, | |
| "unit": null | |
| } | |
| }, | |
| "usage": { | |
| "input_tokens": 174, | |
| "output_tokens": 0 | |
| } | |
| }, | |
| "photo": { | |
| "answers": { | |
| "cats": { | |
| "type": "number", | |
| "number": 2.0, | |
| "interval": [ | |
| 2.0, | |
| 2.0 | |
| ], | |
| "unit": null | |
| }, | |
| "remote": { | |
| "type": "box", | |
| "box": { | |
| "top": 0.155, | |
| "bottom": 0.244, | |
| "left": 0.063, | |
| "right": 0.276 | |
| }, | |
| "found": 1.0, | |
| "confidence": 0.9846427841522876 | |
| }, | |
| "every_cat": { | |
| "type": "boxes", | |
| "boxes": [ | |
| { | |
| "box": { | |
| "top": 0.114, | |
| "bottom": 0.987, | |
| "left": 0.019, | |
| "right": 0.497 | |
| }, | |
| "found": 1.0, | |
| "confidence": 0.9977011494252873 | |
| }, | |
| { | |
| "box": { | |
| "top": 0.053, | |
| "bottom": 0.777, | |
| "left": 0.539, | |
| "right": 0.999 | |
| }, | |
| "found": 0.9942123797283489, | |
| "confidence": 0.9977011494252873 | |
| } | |
| ], | |
| "count": 2, | |
| "at_least": false, | |
| "presence": [ | |
| 1.0, | |
| 0.9942123797283489, | |
| 0.0, | |
| 0.0 | |
| ] | |
| } | |
| }, | |
| "usage": { | |
| "input_tokens": 606, | |
| "output_tokens": 0 | |
| } | |
| }, | |
| "tickets": [ | |
| { | |
| "answers": { | |
| "team": { | |
| "type": "choice", | |
| "choice": "shipping", | |
| "confidence": 0.9922901065236543, | |
| "probabilities": { | |
| "billing": 0.0017408666510449603, | |
| "shipping": 0.9922901065236543, | |
| "technical": 0.005969026825300827 | |
| } | |
| } | |
| }, | |
| "usage": { | |
| "input_tokens": 59, | |
| "output_tokens": 0 | |
| } | |
| }, | |
| { | |
| "answers": { | |
| "team": { | |
| "type": "choice", | |
| "choice": "technical", | |
| "confidence": 0.9938539238861268, | |
| "probabilities": { | |
| "billing": 0.002505713106178254, | |
| "shipping": 0.003640363007695034, | |
| "technical": 0.9938539238861268 | |
| } | |
| } | |
| }, | |
| "usage": { | |
| "input_tokens": 57, | |
| "output_tokens": 0 | |
| } | |
| } | |
| ] | |
| }, | |
| "refusal": { | |
| "type": "ValueError", | |
| "contains": "is longer than the largest the decision backend takes (6144)" | |
| } | |
| } |