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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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  static quants of https://huggingface.co/MaziyarPanahi/Mistral-7B-Instruct-Aya-101
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ base_model: MaziyarPanahi/Mistral-7B-Instruct-Aya-101
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+ datasets:
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+ - CohereForAI/aya_dataset
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+ language:
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+ - afr
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+ - amh
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+ - ara
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+ - aze
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+ - bel
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+ - ben
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+ - bul
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+ - cat
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+ - ceb
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+ - ces
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+ - cym
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+ - dan
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+ - deu
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+ - ell
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+ - eng
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+ - epo
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+ - est
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+ - eus
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+ - fin
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+ - fil
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+ - fra
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+ - fry
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+ - gla
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+ - gle
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+ - glg
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+ - guj
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+ - hat
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+ - hau
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+ - heb
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+ - hin
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+ - hun
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+ - hye
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+ - ibo
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+ - ind
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+ - isl
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+ - ita
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+ - jav
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+ - jpn
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+ - kan
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+ - kat
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+ - kaz
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+ - khm
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+ - kir
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+ - kor
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+ - kur
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+ - lao
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+ - lav
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+ - lat
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+ - lit
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+ - ltz
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+ - mal
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+ - mar
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+ - mkd
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+ - mlg
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+ - mlt
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+ - mon
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+ - mri
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+ - msa
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+ - mya
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+ - nep
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+ - nld
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+ - nor
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+ - nso
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+ - nya
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+ - ory
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+ - pan
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+ - pes
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+ - pol
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+ - por
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+ - pus
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+ - ron
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+ - rus
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+ - sin
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+ - slk
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+ - slv
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+ - smo
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+ - sna
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+ - snd
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+ - som
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+ - sot
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+ - spa
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+ - sqi
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+ - srp
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+ - sun
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+ - swa
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+ - swe
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+ - tam
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+ - tel
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+ - tgk
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+ - tha
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+ - tur
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+ - twi
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+ - ukr
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+ - urd
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+ - uzb
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+ - vie
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+ - xho
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+ - yid
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+ - yor
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+ - zho
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+ - zul
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+ library_name: transformers
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+ license: apache-2.0
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+ quantized_by: mradermacher
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+ tags:
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+ - axolotl
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+ - mistral
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+ - 7b
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+ - generated_from_trainer
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+ ---
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+ ## About
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+
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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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  static quants of https://huggingface.co/MaziyarPanahi/Mistral-7B-Instruct-Aya-101
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+
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+ <!-- provided-files -->
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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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+
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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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+
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+ ## Provided Quants
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+
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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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+
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+ | Link | Type | Size/GB | Notes |
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+ |:-----|:-----|--------:|:------|
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+ | [GGUF](https://huggingface.co/mradermacher/Mistral-7B-Instruct-Aya-101-GGUF/resolve/main/Mistral-7B-Instruct-Aya-101.Q2_K.gguf) | Q2_K | 2.8 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Mistral-7B-Instruct-Aya-101-GGUF/resolve/main/Mistral-7B-Instruct-Aya-101.Q3_K_S.gguf) | Q3_K_S | 3.3 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Mistral-7B-Instruct-Aya-101-GGUF/resolve/main/Mistral-7B-Instruct-Aya-101.Q3_K_M.gguf) | Q3_K_M | 3.6 | lower quality |
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+ | [GGUF](https://huggingface.co/mradermacher/Mistral-7B-Instruct-Aya-101-GGUF/resolve/main/Mistral-7B-Instruct-Aya-101.Q3_K_L.gguf) | Q3_K_L | 3.9 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Mistral-7B-Instruct-Aya-101-GGUF/resolve/main/Mistral-7B-Instruct-Aya-101.IQ4_XS.gguf) | IQ4_XS | 4.0 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Mistral-7B-Instruct-Aya-101-GGUF/resolve/main/Mistral-7B-Instruct-Aya-101.Q4_0_4_4.gguf) | Q4_0_4_4 | 4.2 | fast on arm, low quality |
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+ | [GGUF](https://huggingface.co/mradermacher/Mistral-7B-Instruct-Aya-101-GGUF/resolve/main/Mistral-7B-Instruct-Aya-101.Q4_K_S.gguf) | Q4_K_S | 4.2 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/Mistral-7B-Instruct-Aya-101-GGUF/resolve/main/Mistral-7B-Instruct-Aya-101.Q4_K_M.gguf) | Q4_K_M | 4.5 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/Mistral-7B-Instruct-Aya-101-GGUF/resolve/main/Mistral-7B-Instruct-Aya-101.Q5_K_S.gguf) | Q5_K_S | 5.1 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Mistral-7B-Instruct-Aya-101-GGUF/resolve/main/Mistral-7B-Instruct-Aya-101.Q5_K_M.gguf) | Q5_K_M | 5.2 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Mistral-7B-Instruct-Aya-101-GGUF/resolve/main/Mistral-7B-Instruct-Aya-101.Q6_K.gguf) | Q6_K | 6.0 | very good quality |
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+ | [GGUF](https://huggingface.co/mradermacher/Mistral-7B-Instruct-Aya-101-GGUF/resolve/main/Mistral-7B-Instruct-Aya-101.Q8_0.gguf) | Q8_0 | 7.8 | fast, best quality |
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+ | [GGUF](https://huggingface.co/mradermacher/Mistral-7B-Instruct-Aya-101-GGUF/resolve/main/Mistral-7B-Instruct-Aya-101.f16.gguf) | f16 | 14.6 | 16 bpw, overkill |
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+
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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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+
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+ ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
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+
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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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+
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+ ## FAQ / Model Request
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+
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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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+
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+ ## Thanks
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+
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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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+
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+ <!-- end -->