107 lines
4.7 KiB
Markdown
107 lines
4.7 KiB
Markdown
---
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base_model: LeroyDyer/WORLD_ARCHIVES_II
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datasets:
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- gretelai/synthetic_text_to_sql
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- HuggingFaceTB/cosmopedia
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- teknium/OpenHermes-2.5
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- Open-Orca/SlimOrca
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- Open-Orca/OpenOrca
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- cognitivecomputations/dolphin-coder
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- databricks/databricks-dolly-15k
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- yahma/alpaca-cleaned
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- uonlp/CulturaX
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- mwitiderrick/SwahiliPlatypus
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- swahili
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- Rogendo/English-Swahili-Sentence-Pairs
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- ise-uiuc/Magicoder-Evol-Instruct-110K
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- meta-math/MetaMathQA
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- abacusai/ARC_DPO_FewShot
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- abacusai/MetaMath_DPO_FewShot
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- abacusai/HellaSwag_DPO_FewShot
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- HaltiaAI/Her-The-Movie-Samantha-and-Theodore-Dataset
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- HuggingFaceFW/fineweb
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- occiglot/occiglot-fineweb-v0.5
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- omi-health/medical-dialogue-to-soap-summary
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- keivalya/MedQuad-MedicalQnADataset
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- ruslanmv/ai-medical-dataset
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- Shekswess/medical_llama3_instruct_dataset_short
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- ShenRuililin/MedicalQnA
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- virattt/financial-qa-10K
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- PatronusAI/financebench
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- takala/financial_phrasebank
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- Replete-AI/code_bagel
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- athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW
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- IlyaGusev/gpt_roleplay_realm
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- rickRossie/bluemoon_roleplay_chat_data_300k_messages
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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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- mistral
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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/LeroyDyer/WORLD_ARCHIVES_II
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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/WORLD_ARCHIVES_II-GGUF/resolve/main/WORLD_ARCHIVES_II.Q2_K.gguf) | Q2_K | 2.8 | |
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| [GGUF](https://huggingface.co/mradermacher/WORLD_ARCHIVES_II-GGUF/resolve/main/WORLD_ARCHIVES_II.IQ3_XS.gguf) | IQ3_XS | 3.1 | |
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| [GGUF](https://huggingface.co/mradermacher/WORLD_ARCHIVES_II-GGUF/resolve/main/WORLD_ARCHIVES_II.Q3_K_S.gguf) | Q3_K_S | 3.3 | |
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| [GGUF](https://huggingface.co/mradermacher/WORLD_ARCHIVES_II-GGUF/resolve/main/WORLD_ARCHIVES_II.IQ3_S.gguf) | IQ3_S | 3.3 | beats Q3_K* |
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| [GGUF](https://huggingface.co/mradermacher/WORLD_ARCHIVES_II-GGUF/resolve/main/WORLD_ARCHIVES_II.IQ3_M.gguf) | IQ3_M | 3.4 | |
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| [GGUF](https://huggingface.co/mradermacher/WORLD_ARCHIVES_II-GGUF/resolve/main/WORLD_ARCHIVES_II.Q3_K_M.gguf) | Q3_K_M | 3.6 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/WORLD_ARCHIVES_II-GGUF/resolve/main/WORLD_ARCHIVES_II.Q3_K_L.gguf) | Q3_K_L | 3.9 | |
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| [GGUF](https://huggingface.co/mradermacher/WORLD_ARCHIVES_II-GGUF/resolve/main/WORLD_ARCHIVES_II.IQ4_XS.gguf) | IQ4_XS | 4.0 | |
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| [GGUF](https://huggingface.co/mradermacher/WORLD_ARCHIVES_II-GGUF/resolve/main/WORLD_ARCHIVES_II.Q4_K_S.gguf) | Q4_K_S | 4.2 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/WORLD_ARCHIVES_II-GGUF/resolve/main/WORLD_ARCHIVES_II.Q4_K_M.gguf) | Q4_K_M | 4.5 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/WORLD_ARCHIVES_II-GGUF/resolve/main/WORLD_ARCHIVES_II.Q5_K_S.gguf) | Q5_K_S | 5.1 | |
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| [GGUF](https://huggingface.co/mradermacher/WORLD_ARCHIVES_II-GGUF/resolve/main/WORLD_ARCHIVES_II.Q5_K_M.gguf) | Q5_K_M | 5.2 | |
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| [GGUF](https://huggingface.co/mradermacher/WORLD_ARCHIVES_II-GGUF/resolve/main/WORLD_ARCHIVES_II.Q6_K.gguf) | Q6_K | 6.0 | very good quality |
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| [GGUF](https://huggingface.co/mradermacher/WORLD_ARCHIVES_II-GGUF/resolve/main/WORLD_ARCHIVES_II.Q8_0.gguf) | Q8_0 | 7.8 | fast, best quality |
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| [GGUF](https://huggingface.co/mradermacher/WORLD_ARCHIVES_II-GGUF/resolve/main/WORLD_ARCHIVES_II.f16.gguf) | f16 | 14.6 | 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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