cstr/omniasr-llm-300m-v2-GGUF overview
OmniASR LLM 300M — GGUF GGUF conversion of facebook/omniASR LLM 300M https://huggingface.co/facebook/omniASR LLM 300M for use with CrispASR https://github.com/…
Runs locally from ~1018.2 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
| Model ID | cstr/omniasr-llm-300m-v2-GGUF |
|---|---|
| Author | cstr |
| Pipeline | automatic-speech-recognition |
| License | apache-2.0 |
| Base model | facebook/omniASR-LLM-300M |
| Last modified | 2026-08-02T15:34:23.000Z |
Model README
---
license: apache-2.0
language:
- en
- multilingual
tags:
- speech
- asr
- gguf
- ggml
- omniasr
pipeline_tag: automatic-speech-recognition
base_model: facebook/omniASR-LLM-300M
---
OmniASR LLM-300M — GGUF
GGUF conversion of facebook/omniASR-LLM-300M for use with CrispASR.
OmniASR is Meta's multilingual ASR model family supporting 1600+ languages. Apache-2.0 license.
Autoregressive LLM decoder with language conditioning. Near-perfect English output.
Files
| File | Size |
| --- | ---: |
| omniasr-llm-300m-v2-f16.gguf | 3.0 GB |
| omniasr-llm-300m-v2-q4_k.gguf | 1018 MB |
| omniasr-llm-300m-v2-q8_0.gguf | 1.7 GB |
Quick Start
git clone https://github.com/CrispStrobe/CrispASR && cd CrispASR
cmake -B build -DCMAKE_BUILD_TYPE=Release && cmake --build build -j$(nproc)
./build/bin/crispasr --backend omniasr-llm -m auto --auto-download -f audio.wav
Conversion
Converted using CrispASR's converter scripts with fixed positional conv weight normalization (per-kernel-position norm, not per-output-channel).
Provenance and EU AI Act Art. 53 note
- Upstream model: facebook/omniASR-LLM-300M — 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/GGML). 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.
Run cstr/omniasr-llm-300m-v2-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models