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cstr/wav2vec2-base-960h-GGUF overview

wav2vec2 base 960h — GGUF GGUF conversion of facebook/wav2vec2 base 960h https://huggingface.co/facebook/wav2vec2 base 960h for CrispASR https://github.com/Cri…

ggufasrspeech-recognitionctcforced-alignmentwav2vec2crispasrautomatic-speech-recognitionenbase_model:facebook/wav2vec2-base-960hbase_model:quantized:facebook/wav2vec2-base-960hlicense:apache-2.0region:us

Runs locally from ~197.4 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
107
Likes
1
Pipeline
automatic-speech-recognition
Author

Repository Files & Downloads

1 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
wav2vec2-base-960h.ggufGGUFGGUF197.4 MBDownload

Model Details

Model IDcstr/wav2vec2-base-960h-GGUF
Authorcstr
Pipelineautomatic-speech-recognition
Licenseapache-2.0
Base modelfacebook/wav2vec2-base-960h
Last modified2026-08-02T15:43:40.000Z

Model README

---

language: en

license: apache-2.0

tags:

- gguf

- asr

- speech-recognition

- ctc

- forced-alignment

- wav2vec2

- crispasr

base_model: facebook/wav2vec2-base-960h

pipeline_tag: automatic-speech-recognition

---

wav2vec2-base-960h — GGUF

GGUF conversion of facebook/wav2vec2-base-960h for CrispASR.

This model is primarily used as a CTC forced aligner — it produces word-level timestamps by aligning a known transcript to audio. It can also perform standalone ASR via CTC greedy decode.

Architecture

  • wav2vec2-base: 12-layer transformer encoder (768-dim, 12 heads)
  • CTC head: Linear(768, 32) — character-level English vocabulary
  • Feature extractor: 7-layer CNN (raw waveform -> 512-dim features)
  • Input: 16 kHz mono audio
  • Training: 960 hours of LibriSpeech (supervised CTC fine-tune)

Files

| File | Size | Description |

|------|------|-------------|

| wav2vec2-base-960h.gguf | 197 MB | Full precision (F16 weights, F32 norms) |

Usage with CrispASR

Forced alignment (word-level timestamps)

# Align a transcript to audio — produces word-level SRT:
crispasr --align-only \
    -am wav2vec2-base-960h.gguf \
    -f audio.wav \
    --ref-text "The quick brown fox jumps over the lazy dog." \
    --align-format srt --align-output aligned.srt

# Or align from an existing SRT (re-time the cues):
crispasr --align-only \
    -am wav2vec2-base-960h.gguf \
    -f audio.wav \
    --text-file subtitles.srt \
    --align-output retimed.srt

As an aligner companion for LLM ASR backends

# Word timestamps for any backend that lacks native ones:
crispasr --backend granite -m auto \
    -am wav2vec2-base-960h.gguf --force-aligner \
    -f audio.wav -osrt

Auto-download

# The aligner is auto-downloaded when using -am auto:
crispasr --backend granite -m auto \
    -am auto --force-aligner \
    -f audio.wav -osrt

License

Apache 2.0 (same as the original model).

Credits

Provenance and EU AI Act Art. 53 note

  • Upstream model: facebook/wav2vec2-base-960h — published by facebook.
  • Upstream licence: apache-2.0. This repository redistributes under the same terms; it grants no rights the upstream licence does not.
  • What was done here: format conversion and/or quantisation only (GGUF). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs.
  • Training data: documented — where it is documented at all — by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository.
  • Provider status: under Regulation (EU) 2024/1689 the upstream authors remain the provider of this model. Converting the serialisation format does not make this repository the provider of a new general-purpose AI model, and no such claim is made. Questions about training content, copyright policy or model capability belong upstream.

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