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Independent publisher

Nikita Davidchuk

Ar4ikov

nlp, web, opensource, transformers, asr, ser, tts, cv

Models in Library5
Datasets in Library0
Models on Hugging Face62
Followers22

Compare the published evidence

This profile connects the 5 model and dataset records shown below to their upstream cards and sources. The library counts describe SAVRN's coverage, rather than this publisher's entire output.

Published tasks: Speech recognition, Text classification.

Reported licenses: apache-2.0, mit. Open a record to review its specific license and conditions.

Compare model specifications, source dates, and hardware estimates on the individual records. Publisher identity verification is separate from a model's quality, deployment readiness, or suitability for your work.

Models

Model · Speech recognition

VibeVoice-ASR-DFlash2

Nikita Davidchuk

VibeVoice-ASR (7B), the original BF16 weights as Microsoft published them, with its DFlash 2 drafter bundled in drafter/: one download, and vibevoice.c decodes with speculative decoding -- the drafter proposes 8 tokens in one pass, the model checks them in one pass and keeps the ones it agrees with. the model's own decode step, so the transcript is byte-for-byte the one without the drafter. (With a drafter vibevoice.c attends with flashinfer, which checks rows together; the transcript is then --attn flashinfer's.) Needs vibevoice.c with DFlash 2 support: branch dflash2 (PR #48), in the next release. A model directory's drafter/ is used without asking: vibevoice.c runs BF16 weights as dense…

Open weights mit 8.7B parameters vibevoice.c

VibeVoice-ASR (7B), AWQ W4A16 (asymmetric, groups of 128), with its DFlash 2 drafter bundled in drafter/: one download, and vibevoice.c decodes with speculative decoding -- the drafter proposes 8 tokens in one pass, the model checks them in one pass and keeps the ones it agrees with. the model's own decode step, so the transcript is byte-for-byte the one without the drafter. (With a drafter vibevoice.c attends with flashinfer, which checks rows together; the transcript is then --attn flashinfer's.) Needs vibevoice.c with DFlash 2 support: branch dflash2 (PR #48), in the next release. A model directory's drafter/ is used without asking: vibevoice.c b72be15 (branch dflash2), RTX 3090, greedy…

Open weights mit 8.3B parameters vibevoice.c

A DFlash 2 block drafter for VibeVoice-ASR (7B) (Ar4ikov/VibeVoice-ASR-AWQ-W4A16-ASYM), for speculative decoding in vibevoice.c. It proposes 8 tokens in one pass; vibevoice.c checks them in one pass of the model and keeps the ones the model agrees with, plus one of its own. the model's own one-token decode step, so the transcript with this drafter is byte-for-byte the transcript without it — words, timestamps, speakers. The drafter only changes how many passes it takes. One thing changes with --draft: vibevoice.c then attends with flashinfer (--attn auto picks it), because flashinfer checks several rows in one pass over the cache where the default fa2 walks it once per row. The transcript…

Open weights mit 832M parameters 131,072 tokens vibevoice.c

Model · Speech recognition

VibeVoice-ASR-DFlash2-Drafter

Nikita Davidchuk

A DFlash 2 block drafter for VibeVoice-ASR (7B) (Ar4ikov/VibeVoice-ASR-AWQ-W4A16-ASYM), for speculative decoding in vibevoice.c. It proposes 8 tokens in one pass; vibevoice.c checks them in one pass of the model and keeps the ones the model agrees with, plus one of its own. the model's own one-token decode step, so the transcript with this drafter is byte-for-byte the transcript without it — words, timestamps, speakers. The drafter only changes how many passes it takes. One thing changes with --draft: vibevoice.c then attends with flashinfer (--attn auto picks it), because flashinfer checks several rows in one pass over the cache where the default fa2 walks it once per row. The transcript…

Open weights mit 831M parameters 131,072 tokens vibevoice.c

Model · Text classification

decider-4b-AWQ-ASYM-W4A16

Nikita Davidchuk

Activation-aware asymmetric INT4 weight-only quantization of Mapika/decider-4b, revision 99d7fd5bfcc4d11ba37239dafe0ed653803819d3. This is a typed decision model: read probabilities over specified options in one forward pass. It is not trained for conversational text generation. llm-compressor 0.12.0.1, Transformers 5.10.1, PyTorch 2.12.0+cu130. AWQ scaling followed by QuantizationModifier, scheme W4A16ASYM, group size 128, asymmetric integer weights, BF16 activations. savecompressed=True produces physical weightpacked tensors in compressed-tensors format. All Linear layers are targeted except lmhead, linearattn.inproja, linearattn.inprojb, and MTP (if present). Embeddings, norms…

Open weights apache-2.0 4.2B parameters 262,144 tokens transformers