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Model: mradermacher/lemura-arabic-asr-qwen3-GGUF Source: Original Platform
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---
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base_model: lemuralabs/lemura-arabic-asr-qwen3
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datasets:
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- MohamedRashad/SADA22
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- MohamedRashad/MASC-Arabic
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- google/fleurs
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- fsicoli/common_voice_17_0
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language:
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- ar
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- arz
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- apc
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- ary
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- afb
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- acm
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library_name: transformers
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license: apache-2.0
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mradermacher:
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readme_rev: 1
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quantized_by: mradermacher
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tags:
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- automatic-speech-recognition
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- speech-recognition
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- speech-to-text
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- stt
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- transcription
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- speech
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- audio
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- asr
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- arabic
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- arabic-asr
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- arabic-speech
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- dialectal-arabic
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- msa
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- modern-standard-arabic
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- gulf-arabic
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- khaleeji
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- egyptian-arabic
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- levantine-arabic
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- iraqi-arabic
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- maghrebi-arabic
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- darija
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- multi-dialect
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- code-switching
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- qwen3-asr
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- qwen3
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- audio-llm
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- generative-asr
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- lora
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- fine-tuned
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---
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## About
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<!-- ### quantize_version: 2 -->
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<!-- ### output_tensor_quantised: 1 -->
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<!-- ### convert_type: hf -->
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<!-- ### vocab_type: -->
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<!-- ### tags: -->
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<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
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<!-- ### quants_skip: -->
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<!-- ### skip_mmproj: -->
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static quants of https://huggingface.co/lemuralabs/lemura-arabic-asr-qwen3
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<!-- provided-files -->
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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#lemura-arabic-asr-qwen3-GGUF).***
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weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
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## Usage
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If you are unsure how to use GGUF files, refer to one of [TheBloke's
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READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
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more details, including on how to concatenate multi-part files.
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## Provided Quants
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(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
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| Link | Type | Size/GB | Notes |
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|:-----|:-----|--------:|:------|
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| [GGUF](https://huggingface.co/mradermacher/lemura-arabic-asr-qwen3-GGUF/resolve/main/lemura-arabic-asr-qwen3.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 0.5 | multi-modal supplement |
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| [GGUF](https://huggingface.co/mradermacher/lemura-arabic-asr-qwen3-GGUF/resolve/main/lemura-arabic-asr-qwen3.mmproj-f16.gguf) | mmproj-f16 | 0.7 | multi-modal supplement |
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| [GGUF](https://huggingface.co/mradermacher/lemura-arabic-asr-qwen3-GGUF/resolve/main/lemura-arabic-asr-qwen3.Q2_K.gguf) | Q2_K | 0.9 | |
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| [GGUF](https://huggingface.co/mradermacher/lemura-arabic-asr-qwen3-GGUF/resolve/main/lemura-arabic-asr-qwen3.Q3_K_S.gguf) | Q3_K_S | 1.0 | |
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| [GGUF](https://huggingface.co/mradermacher/lemura-arabic-asr-qwen3-GGUF/resolve/main/lemura-arabic-asr-qwen3.Q3_K_M.gguf) | Q3_K_M | 1.0 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/lemura-arabic-asr-qwen3-GGUF/resolve/main/lemura-arabic-asr-qwen3.Q3_K_L.gguf) | Q3_K_L | 1.1 | |
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| [GGUF](https://huggingface.co/mradermacher/lemura-arabic-asr-qwen3-GGUF/resolve/main/lemura-arabic-asr-qwen3.IQ4_XS.gguf) | IQ4_XS | 1.1 | |
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| [GGUF](https://huggingface.co/mradermacher/lemura-arabic-asr-qwen3-GGUF/resolve/main/lemura-arabic-asr-qwen3.Q4_K_S.gguf) | Q4_K_S | 1.2 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/lemura-arabic-asr-qwen3-GGUF/resolve/main/lemura-arabic-asr-qwen3.Q4_K_M.gguf) | Q4_K_M | 1.2 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/lemura-arabic-asr-qwen3-GGUF/resolve/main/lemura-arabic-asr-qwen3.Q5_K_S.gguf) | Q5_K_S | 1.3 | |
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| [GGUF](https://huggingface.co/mradermacher/lemura-arabic-asr-qwen3-GGUF/resolve/main/lemura-arabic-asr-qwen3.Q5_K_M.gguf) | Q5_K_M | 1.4 | |
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| [GGUF](https://huggingface.co/mradermacher/lemura-arabic-asr-qwen3-GGUF/resolve/main/lemura-arabic-asr-qwen3.Q6_K.gguf) | Q6_K | 1.5 | very good quality |
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| [GGUF](https://huggingface.co/mradermacher/lemura-arabic-asr-qwen3-GGUF/resolve/main/lemura-arabic-asr-qwen3.Q8_0.gguf) | Q8_0 | 1.9 | fast, best quality |
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| [GGUF](https://huggingface.co/mradermacher/lemura-arabic-asr-qwen3-GGUF/resolve/main/lemura-arabic-asr-qwen3.f16.gguf) | f16 | 3.5 | 16 bpw, overkill |
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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types (lower is better):
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And here are Artefact2's thoughts on the matter:
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https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
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## FAQ / Model Request
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See https://huggingface.co/mradermacher/model_requests for some answers to
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questions you might have and/or if you want some other model quantized.
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## Thanks
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I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
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me use its servers and providing upgrades to my workstation to enable
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this work in my free time.
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<!-- end -->
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