nemotron-transcribe

Invocation: /nemotron-transcribe.

Use this skill as the reference desk and workflow router for NVIDIA Nemotron 3.5 Transcribe. Keep NeMo Speech as the source of truth for executable speech training and export procedures.

Start here

1. Read INDEX.md to locate the smallest relevant source.
2. Use context/quick-reference.md for fast routing.
3. Use model-card.md for identity, variants, capabilities, and inference boundaries.
4. Use recipes/overview.md to select an available upstream workflow and see which stages are still missing.
5. For deployment examples, read usage-cookbook/Nemotron-3.5-Transcribe/README.md from the repository root.

Source priority

Resolve conflicts in this order:

1. the selected checkpoint's Hugging Face model card;
2. the canonical NeMo Speech skill and implementation for the requested stage;
3. the technical report for model-development, architecture, and reported-evaluation claims;
4. this skill's compact summaries;
5. the Nemotron cookbook.

Cite the stable report URL above only after it is publicly accessible.

Use the BF16 model card while planning fine-tuning and the destination precision's model card while planning deployment. The model cards define serving flags per precision; do not merge BF16, FP8, and NVFP4 launch settings into a single assumed profile.

Route operational requests

When routing, give the relevant stage order and prerequisites first, then point to the upstream skill. Do not reproduce its detailed procedure locally.

Precision selection

• BF16 is the reference checkpoint and the starting point for fine-tuning.
• FP8 is a ModelOpt export with quantized decoder, audio encoder, and MTP head. Let the serving stack read its quantization configuration.
• NVFP4 is a mixed NVFP4/FP8 export and requires Blackwell. It uses an explicit FP8 KV cache in the validated profile.

Name the exact model ID and precision in every serving or evaluation answer. Do not imply that a quantized release is the preferred training source. When a user fine-tunes BF16 and then requests FP8 or NVFP4, route them to quantize their merged customized checkpoint. The published quantized releases are quantizations of NVIDIA's released BF16 model, not of the user's fine-tune.

Inference rules worth surfacing

• The model is offline and supports recordings up to the one-hour training limit; internal 30-second chunks are not streaming.
• For transcription, translation, and language identification, start with reasoning disabled and temperature 0.
• Preserve special tokens for speaker and event tags.
• Timestamp output is optional metadata. Check its error field before using word alignments, and keep the request to one audio, one non-streaming completion.
• MTP and DFlash2 are alternatives. Current DFlash2 serving does not combine with CTC timestamps.
• Smoke-test MTP and CTC timestamps on the merged BF16 fine-tune before quantization, then test them again after assembly and quantization.
• Prefer the selected model card's validated speculative-decoding profile over an illustrative default in a generic stage guide.
• Treat NeMo Speech and the checkpoint as one compatibility bundle. Current checkpoints use Nemotron3_5TranscribeForConditionalGeneration; they require a NeMo Speech revision that registers that architecture and its Nemotron3_5TranscribeMTPModel draft. Old/old pairs may still work, but do not mix pre-rename and post-rename components.
• Pin the GPU-tested NeMo Speech and checkpoint revisions; main and an unqualified model ID are moving dependencies.

Answering style

• Start with the direct answer.
• Distinguish model-card claims, technical-report results, and public recipe coverage as separate source layers.
• Link the exact upstream skill, script, or guide used.
• State public gaps plainly. Never invent a checkpoint, dataset, stage config, or release pin.
• For exhaustive benchmark numbers, prompt lists, language coverage, safety, and licensing, link the model card instead of copying it.

Boundaries

Do:

• provide model-specific routing, stage ordering, variant selection, and known compatibility constraints;
• distinguish main-stage construction from released-checkpoint adaptation and from exact release reproduction;
• use NeMo Speech for speech-model implementation details;
• use the Nemotron cookbook for concise deployment examples.

Do not:

• paste or fork the NeMo Speech operational skills into this directory;
• fill the main-stage template's production placeholders with guessed values or present it as the exact released-checkpoint recipe;
• claim that timestamp serving is a timestamp-head training recipe;
• claim public RL reproduction until a maintained Transcribe recipe exists;
• apply generic LLM fine-tuning guidance when the speech checkpoint's encoder, projection, auxiliary heads, and prompt format must be preserved;
• expose credentials or internal paths, or publish a checkpoint revision before confirming that the corresponding artifact is public.