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Model: mradermacher/tinyllama-3T-128k-JsonExtract-GGUF Source: Original Platform
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tinyllama-3T-128k-JsonExtract.IQ4_XS.gguf filter=lfs diff=lfs merge=lfs -text
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---
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base_model: muzammil-eds/tinyllama-3T-128k-JsonExtract
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language:
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- en
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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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- text-generation-inference
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- transformers
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- unsloth
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- llama
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- trl
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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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static quants of https://huggingface.co/muzammil-eds/tinyllama-3T-128k-JsonExtract
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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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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/tinyllama-3T-128k-JsonExtract-GGUF/resolve/main/tinyllama-3T-128k-JsonExtract.Q2_K.gguf) | Q2_K | 0.5 | |
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| [GGUF](https://huggingface.co/mradermacher/tinyllama-3T-128k-JsonExtract-GGUF/resolve/main/tinyllama-3T-128k-JsonExtract.Q3_K_S.gguf) | Q3_K_S | 0.6 | |
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| [GGUF](https://huggingface.co/mradermacher/tinyllama-3T-128k-JsonExtract-GGUF/resolve/main/tinyllama-3T-128k-JsonExtract.Q3_K_M.gguf) | Q3_K_M | 0.6 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/tinyllama-3T-128k-JsonExtract-GGUF/resolve/main/tinyllama-3T-128k-JsonExtract.Q3_K_L.gguf) | Q3_K_L | 0.7 | |
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| [GGUF](https://huggingface.co/mradermacher/tinyllama-3T-128k-JsonExtract-GGUF/resolve/main/tinyllama-3T-128k-JsonExtract.IQ4_XS.gguf) | IQ4_XS | 0.7 | |
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| [GGUF](https://huggingface.co/mradermacher/tinyllama-3T-128k-JsonExtract-GGUF/resolve/main/tinyllama-3T-128k-JsonExtract.Q4_K_S.gguf) | Q4_K_S | 0.7 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/tinyllama-3T-128k-JsonExtract-GGUF/resolve/main/tinyllama-3T-128k-JsonExtract.Q4_K_M.gguf) | Q4_K_M | 0.8 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/tinyllama-3T-128k-JsonExtract-GGUF/resolve/main/tinyllama-3T-128k-JsonExtract.Q5_K_S.gguf) | Q5_K_S | 0.9 | |
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| [GGUF](https://huggingface.co/mradermacher/tinyllama-3T-128k-JsonExtract-GGUF/resolve/main/tinyllama-3T-128k-JsonExtract.Q5_K_M.gguf) | Q5_K_M | 0.9 | |
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| [GGUF](https://huggingface.co/mradermacher/tinyllama-3T-128k-JsonExtract-GGUF/resolve/main/tinyllama-3T-128k-JsonExtract.Q6_K.gguf) | Q6_K | 1.0 | very good quality |
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| [GGUF](https://huggingface.co/mradermacher/tinyllama-3T-128k-JsonExtract-GGUF/resolve/main/tinyllama-3T-128k-JsonExtract.Q8_0.gguf) | Q8_0 | 1.3 | fast, best quality |
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| [GGUF](https://huggingface.co/mradermacher/tinyllama-3T-128k-JsonExtract-GGUF/resolve/main/tinyllama-3T-128k-JsonExtract.f16.gguf) | f16 | 2.3 | 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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tinyllama-3T-128k-JsonExtract.IQ4_XS.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:e8b3f259d40ce2ef4ec5dc5269e92ccb50c1c6baf492991ed6901c15712404ba
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size 609808288
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oid sha256:b8d7d8cc9d0322f07f248e02c111a61c089a2f05932f50b548b61ef5a2c0797e
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size 432132000
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tinyllama-3T-128k-JsonExtract.Q3_K_L.gguf
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oid sha256:8a89549342f33f5c93cc630368493408b646aef6ba43acec87bdf877e8c24eaf
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size 591527840
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tinyllama-3T-128k-JsonExtract.Q3_K_M.gguf
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oid sha256:1c18749c16f30466b4af7453ca79fb7a4b72745fba5b774b772015c0a4bedb15
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size 548405152
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version https://git-lfs.github.com/spec/v1
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oid sha256:9782f8b8737d3e544cc32277aedd982c94fb1dbcd11524259b8f14611287075d
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size 499343264
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oid sha256:3335444080537426d4ced150c3a6c86bc0383db40795fa2e553e7ea32550c127
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size 667815840
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oid sha256:688e1b19a02e0922c4348d8e95fae4fdebd469382e3a0bae306778906f57ac47
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size 639872928
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oid sha256:8c5152838097490d3e6487c4eb53a7f3cfb6f82d0ca9c8b82095d4aa8a616c4e
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size 782045088
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oid sha256:3ee067f13e0f22ccea2bbc60d28c24057a3c4b6563c5ed32fcdb6303c755f06d
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size 766029728
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oid sha256:cd98e7466875bba5024ce1e370433544f0df3467f3c6a953f2cc321648dd7f93
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size 903413664
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oid sha256:12e51a4e553c2d5c0a2ae94ad3f29f2bc68b8be791979af2d17192a8c0545caa
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size 1169809312
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oid sha256:bc15b12eaecadb06120f924a07ed341e3985cfc841d699ff84f4e37eeae3444a
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size 2201018272
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