ibm-granite/granite-speech-4.1-2b-nar
feature-extraction model by ibm-granite
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Model card & documentation
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Model Summary: Granite-Speech-4.1-2B-NAR is a non-autoregressive (NAR) speech recognition model that formulates ASR as conditional transcript editing. Instead of decoding tokens one at a time, it edits a CTC hypothesis in a single forward pass using a bidirectional LLM, achieving competitive accuracy with faster inference than autoregressive alternatives. The model is based on the NLE (Non-autoregressive LLM-based Editing) architecture described in this paper. For applications where accuracy is the primary concern, consider granite-speech-4.1-2b, an autoregressive model from the Granite Speech 4.1 family which achieves higher transcription accuracy at the cost of increased inference latency. Granite-speech-4.1-2b produces punctuated and capitalized transcripts, supports AST and keyword-biased recognition, and includes Japanese. When speaker or word-timing information is needed, consider using granite-speech-4.1-2b-plus, which extends the above model with speaker-attributed ASR (speaker labels + word transcripts) and word-level timing information. Release Date: April 2026 License: Apache 2.0 Supported Languages: English, French, German, Spanish, Portuguese Intended…
Read the full model card ↗ · Preview checked 2026-10-31T14:03:21.111Z
Inside the original model card — Document outline
- Granite-Speech-4.1-2B-NAR
- Evaluation Results
- Open ASR leaderboard results
- Additional results
- Usage
- Installation
- Inference with transformers
- Model Architecture
- How Granite-speech NAR Works
- Training Data
- Infrastructure
- Ethical Considerations and Limitations
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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
ibm-granite/granite-speech-4.1-2b-nar is a feature-extraction model repository published by ibm-granite on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- feature-extraction
- Library
- transformers
- Recent downloads (30 days)
- 112,949
- Cumulative likes
- 61
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 2,254,635,356
- Architecture
- GraniteSpeechNarForASR
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-03-10T12:21:20.000Z
- Last modified
- 2026-06-18T07:27:08.000Z
Compatibility and lineage
Reported languages: en, fr, de, es, pt
Reported base models: ibm-granite/granite-4.0-1b-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.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:54:29.511Z. Daily imports are snapshots, not real-time monitoring.
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