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@@ -37,3 +37,11 @@ SearchGym_Qwen_2.5_7B_Instruct.f16.gguf filter=lfs diff=lfs merge=lfs -text
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SearchGym_Qwen_2.5_7B_Instruct.Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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SearchGym_Qwen_2.5_7B_Instruct.Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
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SearchGym_Qwen_2.5_7B_Instruct.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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SearchGym_Qwen_2.5_7B_Instruct.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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SearchGym_Qwen_2.5_7B_Instruct.Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
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SearchGym_Qwen_2.5_7B_Instruct.Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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SearchGym_Qwen_2.5_7B_Instruct.Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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SearchGym_Qwen_2.5_7B_Instruct.Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
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SearchGym_Qwen_2.5_7B_Instruct.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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SearchGym_Qwen_2.5_7B_Instruct.Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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SearchGym_Qwen_2.5_7B_Instruct.Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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SearchGym_Qwen_2.5_7B_Instruct.IQ4_XS.gguf filter=lfs diff=lfs merge=lfs -text
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62
README.md
62
README.md
@@ -1,3 +1,14 @@
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---
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base_model: hkuzxc/SearchGym_Qwen_2.5_7B_Instruct
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language:
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- en
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library_name: transformers
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mradermacher:
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readme_rev: 1
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quantized_by: mradermacher
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---
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## About
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<!-- ### quantize_version: 2 -->
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<!-- ### quantize_version: 2 -->
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<!-- ### output_tensor_quantised: 1 -->
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<!-- ### output_tensor_quantised: 1 -->
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<!-- ### convert_type: hf -->
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<!-- ### convert_type: hf -->
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@@ -7,3 +18,54 @@
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<!-- ### quants_skip: -->
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<!-- ### quants_skip: -->
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<!-- ### skip_mmproj: -->
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<!-- ### skip_mmproj: -->
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static quants of https://huggingface.co/hkuzxc/SearchGym_Qwen_2.5_7B_Instruct
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static quants of https://huggingface.co/hkuzxc/SearchGym_Qwen_2.5_7B_Instruct
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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#SearchGym_Qwen_2.5_7B_Instruct-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/SearchGym_Qwen_2.5_7B_Instruct-GGUF/resolve/main/SearchGym_Qwen_2.5_7B_Instruct.Q2_K.gguf) | Q2_K | 3.1 | |
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| [GGUF](https://huggingface.co/mradermacher/SearchGym_Qwen_2.5_7B_Instruct-GGUF/resolve/main/SearchGym_Qwen_2.5_7B_Instruct.Q3_K_S.gguf) | Q3_K_S | 3.6 | |
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| [GGUF](https://huggingface.co/mradermacher/SearchGym_Qwen_2.5_7B_Instruct-GGUF/resolve/main/SearchGym_Qwen_2.5_7B_Instruct.Q3_K_M.gguf) | Q3_K_M | 3.9 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/SearchGym_Qwen_2.5_7B_Instruct-GGUF/resolve/main/SearchGym_Qwen_2.5_7B_Instruct.Q3_K_L.gguf) | Q3_K_L | 4.2 | |
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| [GGUF](https://huggingface.co/mradermacher/SearchGym_Qwen_2.5_7B_Instruct-GGUF/resolve/main/SearchGym_Qwen_2.5_7B_Instruct.IQ4_XS.gguf) | IQ4_XS | 4.4 | |
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| [GGUF](https://huggingface.co/mradermacher/SearchGym_Qwen_2.5_7B_Instruct-GGUF/resolve/main/SearchGym_Qwen_2.5_7B_Instruct.Q4_K_S.gguf) | Q4_K_S | 4.6 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/SearchGym_Qwen_2.5_7B_Instruct-GGUF/resolve/main/SearchGym_Qwen_2.5_7B_Instruct.Q4_K_M.gguf) | Q4_K_M | 4.8 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/SearchGym_Qwen_2.5_7B_Instruct-GGUF/resolve/main/SearchGym_Qwen_2.5_7B_Instruct.Q5_K_S.gguf) | Q5_K_S | 5.4 | |
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| [GGUF](https://huggingface.co/mradermacher/SearchGym_Qwen_2.5_7B_Instruct-GGUF/resolve/main/SearchGym_Qwen_2.5_7B_Instruct.Q5_K_M.gguf) | Q5_K_M | 5.5 | |
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| [GGUF](https://huggingface.co/mradermacher/SearchGym_Qwen_2.5_7B_Instruct-GGUF/resolve/main/SearchGym_Qwen_2.5_7B_Instruct.Q6_K.gguf) | Q6_K | 6.4 | very good quality |
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| [GGUF](https://huggingface.co/mradermacher/SearchGym_Qwen_2.5_7B_Instruct-GGUF/resolve/main/SearchGym_Qwen_2.5_7B_Instruct.Q8_0.gguf) | Q8_0 | 8.2 | fast, best quality |
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| [GGUF](https://huggingface.co/mradermacher/SearchGym_Qwen_2.5_7B_Instruct-GGUF/resolve/main/SearchGym_Qwen_2.5_7B_Instruct.f16.gguf) | f16 | 15.3 | 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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version https://git-lfs.github.com/spec/v1
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oid sha256:df62001071949c395246cf312376ecde9e9e8d121b85598b125142236ce8df86
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size 4250298784
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version https://git-lfs.github.com/spec/v1
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oid sha256:ef09fdb7087d4baaba31070a35c13d02399772bddba43cc4aa8adec1e20b8be4
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size 4088459680
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version https://git-lfs.github.com/spec/v1
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oid sha256:bdadd6fc7df82bdbd6aff4541cc74f55578ce34d4065e7d385fdeeb0382754d9
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size 3808391584
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3
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version https://git-lfs.github.com/spec/v1
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oid sha256:436f2ec99102f6643fff1aafd9af03b5969de02f3f9042589b92c24ec4baeb77
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size 3492368800
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3
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version https://git-lfs.github.com/spec/v1
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oid sha256:e5574fc1c47fb8b91e2f71c0cb2e9289c6d8e3be876b1b9ca8a2277065d915f9
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size 4683073952
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3
SearchGym_Qwen_2.5_7B_Instruct.Q5_K_M.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:52cce4de2dd9c83084cc5ed22c6c8bb00e1c3e1fb3dbb573a3d019e703131b4c
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size 5444831648
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3
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version https://git-lfs.github.com/spec/v1
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oid sha256:23ecb58dc74c2bda11f9f31eb9f18b2823526a23dba8137951233e7c22d06973
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size 5315176864
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||||||
3
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version https://git-lfs.github.com/spec/v1
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||||||
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oid sha256:5423291f529bf695f7e8e91ff56d05ee4e49150e393230a0fc3daa1b955d8efd
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size 6254199200
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||||||
Reference in New Issue
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