--- base_model: lemuralabs/lemura-arabic-asr-qwen3 datasets: - MohamedRashad/SADA22 - MohamedRashad/MASC-Arabic - google/fleurs - fsicoli/common_voice_17_0 language: - ar - arz - apc - ary - afb - acm library_name: transformers license: apache-2.0 mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - automatic-speech-recognition - speech-recognition - speech-to-text - stt - transcription - speech - audio - asr - arabic - arabic-asr - arabic-speech - dialectal-arabic - msa - modern-standard-arabic - gulf-arabic - khaleeji - egyptian-arabic - levantine-arabic - iraqi-arabic - maghrebi-arabic - darija - multi-dialect - code-switching - qwen3-asr - qwen3 - audio-llm - generative-asr - lora - fine-tuned --- ## About static quants of https://huggingface.co/lemuralabs/lemura-arabic-asr-qwen3 ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#lemura-arabic-asr-qwen3-GGUF).*** 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. ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Provided Quants (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) | Link | Type | Size/GB | Notes | |:-----|:-----|--------:|:------| | [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 | | [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 | | [GGUF](https://huggingface.co/mradermacher/lemura-arabic-asr-qwen3-GGUF/resolve/main/lemura-arabic-asr-qwen3.Q2_K.gguf) | Q2_K | 0.9 | | | [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 | | | [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 | | [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 | | | [GGUF](https://huggingface.co/mradermacher/lemura-arabic-asr-qwen3-GGUF/resolve/main/lemura-arabic-asr-qwen3.IQ4_XS.gguf) | IQ4_XS | 1.1 | | | [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 | | [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 | | [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 | | | [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 | | | [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 | | [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 | | [GGUF](https://huggingface.co/mradermacher/lemura-arabic-asr-qwen3-GGUF/resolve/main/lemura-arabic-asr-qwen3.f16.gguf) | f16 | 3.5 | 16 bpw, overkill | Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better): ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png) And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 ## FAQ / Model Request See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized. ## Thanks I thank my company, [nethype GmbH](https://www.nethype.de/), for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.