nlpctx/activeqa-telugu-reformulator-rl

reinforcement-learning model by nlpctx

Older snapshot: check the original source for current information.

From the publisher

Model card & documentation

Source preview

Read the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.

MultiIndicParaphraseGenerationSS post-trained with a validation-gated RL loop (entity-preservation reward, QA reward l3cube-pune/telugu-question-answering-squad-bert). The LoRA trained directly from the raw checkpoint on 804 Telugu questions, best checkpoint selected on 200 held-out dev questions.…

nlpctx/activeqa-telugu-reformulator-rl on Hugging Face A short preview, not the full document.

Read the full model card ↗ · Preview checked 2026-11-01T04:33:31.386Z

Inside the original model card — Document outline

ActiveQATeluguReformulatorRL (merged LoRA)

Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.

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

Model overview

nlpctx/activeqa-telugu-reformulator-rl is a reinforcement-learning model repository published by nlpctx on Hugging Face. A library was not reported.

This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.

Model facts

Task: reinforcement-learning
Library: Not reported
Recent downloads (30 days): 0
Cumulative likes: 0
Hugging Face trending score: 0
Reported safetensors parameters: 244,082,191
Architecture: MBartForConditionalGeneration
License: mit
Access: Not gated by Hugging Face
Created: 2026-10-27T06:42:10.000Z
Last modified: 2026-10-27T06:42:22.000Z

Compatibility and lineage

Reported languages: te

Base-model lineage was not included.

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.

Use and evaluate

Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.

No model weights are downloaded or executed by AltAPIs. Never enable remote model code without reviewing it.

Model card and usage instructions

Model files and configuration

Community discussion