doofz/THX-01

text-classification model by doofz

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THX-01 is a non-autoregressive, multilingual decision model developed by HAL-X AI. Given a state (a message, ticket, e-mail, document, JSON record or agent trace) and one or more typed questions written in natural language, it returns a calibrated answer to every question in a single forward pass of about 10 ms on one GPU. THX-01 is trained with large-scale Reinforcement Learning for Calibrated Decisions (RLCD): the reward is a strictly proper scoring rule, so reporting honest probabilities is the only way to maximise it. Beyond choosing among options, THX-01 can return numbers stated in a document, verbatim excerpts and supporting citations, through the same interface. number, excerpt and citations are native THX-01 capabilities. They are not part of the TypeSafe question types (choice, noul, score), where they have to be emulated in the service layer with repeated choice calls. THX-01 also answers such emulation calls (value-range buckets and document chunks)…

doofz/THX-01 on Hugging Face A short preview, not the full document.

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Inside the original model card — Document outline
  1. THX-01
  2. Contents
  3. Question types
  4. Quickstart
  5. Benchmarks
  6. Support-ticket classification
  7. Extraction and citation
  8. Calibration and selective automation
  9. Multilingual decision suite
  10. Speed
  11. Method
  12. Reinforcement Learning for Calibrated Decisions

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Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.

Model overview

doofz/THX-01 is a text-classification model repository published by doofz on Hugging Face. The source reports the thx01 library.

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Model facts

Task
text-classification
Library
thx01
Recent downloads (30 days)
631
Cumulative likes
81
Hugging Face trending score
70
Reported safetensors parameters
321,908,998
Architecture
THXDecisionModel
License
apache-2.0
Access
Not gated by Hugging Face
Created
2026-09-23T12:59:53.000Z
Last modified
2026-10-16T16:22:07.000Z

Compatibility and lineage

Reported languages: az, en, ru, tr, de, fr, es, ar, hi, zh, fa, ka, ja, ko, uk, kk, uz, it, multilingual

Reported base models: jhu-clsp/mmBERT-base

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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Source: Hugging Face Hub. Metadata observed 2026-10-18T06:42:00.150Z. Daily imports are snapshots, not real-time monitoring.

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