	---
	base_model: LeroyDyer/LCARS_AI_014
	datasets:
	- gretelai/synthetic_text_to_sql
	- HuggingFaceTB/cosmopedia
	- teknium/OpenHermes-2.5
	- Open-Orca/SlimOrca
	- Open-Orca/OpenOrca
	- cognitivecomputations/dolphin-coder
	- databricks/databricks-dolly-15k
	- yahma/alpaca-cleaned
	- uonlp/CulturaX
	- mwitiderrick/SwahiliPlatypus
	- swahili
	- Rogendo/English-Swahili-Sentence-Pairs
	- ise-uiuc/Magicoder-Evol-Instruct-110K
	- meta-math/MetaMathQA
	- abacusai/ARC_DPO_FewShot
	- abacusai/MetaMath_DPO_FewShot
	- abacusai/HellaSwag_DPO_FewShot
	- HaltiaAI/Her-The-Movie-Samantha-and-Theodore-Dataset
	- HuggingFaceFW/fineweb
	- occiglot/occiglot-fineweb-v0.5
	- omi-health/medical-dialogue-to-soap-summary
	- keivalya/MedQuad-MedicalQnADataset
	- ruslanmv/ai-medical-dataset
	- Shekswess/medical_llama3_instruct_dataset_short
	- ShenRuililin/MedicalQnA
	- virattt/financial-qa-10K
	- PatronusAI/financebench
	- takala/financial_phrasebank
	- Replete-AI/code_bagel
	- athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW
	- IlyaGusev/gpt_roleplay_realm
	- rickRossie/bluemoon_roleplay_chat_data_300k_messages
	- jtatman/hypnosis_dataset
	- Hypersniper/philosophy_dialogue
	- Locutusque/function-calling-chatml
	- bible-nlp/biblenlp-corpus
	- DatadudeDev/Bible
	- Helsinki-NLP/bible_para
	- HausaNLP/AfriSenti-Twitter
	- aixsatoshi/Chat-with-cosmopedia
	- HuggingFaceTB/cosmopedia-100k
	- HuggingFaceFW/fineweb-edu
	- m-a-p/CodeFeedback-Filtered-Instruction
	- heliosbrahma/mental_health_chatbot_dataset
	language:
	- en
	- sw
	- ig
	- so
	- es
	- ca
	library_name: transformers
	license: apache-2.0
	quantized_by: mradermacher
	tags:
	- text-generation-inference
	- transformers
	- unsloth
	- mistral
	- trl
	- chemistry
	- biology
	- legal
	- art
	- music
	- finance
	- code
	- medical
	- not-for-all-audiences
	- merge
	- climate
	- chain-of-thought
	- tree-of-knowledge
	- forest-of-thoughts
	- visual-spacial-sketchpad
	- alpha-mind
	- knowledge-graph
	- entity-detection
	- encyclopedia
	- wikipedia
	- stack-exchange
	- Reddit
	- Cyber-series
	- MegaMind
	- Cybertron
	- SpydazWeb
	- Spydaz
	- LCARS
	- star-trek
	- mega-transformers
	- Mulit-Mega-Merge
	- Multi-Lingual
	- Afro-Centric
	- African-Model
	- Ancient-One
	---
	## About

	<!-- ### quantize_version: 2 -->
	<!-- ### output_tensor_quantised: 1 -->
	<!-- ### convert_type: hf -->
	<!-- ### vocab_type: -->
	<!-- ### tags: -->
	static quants of https://huggingface.co/LeroyDyer/LCARS_AI_014

	<!-- provided-files -->
	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/LCARS_AI_014-GGUF/resolve/main/LCARS_AI_014.Q2_K.gguf) \| Q2_K \| 2.8 \| \|
	\| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_014-GGUF/resolve/main/LCARS_AI_014.IQ3_XS.gguf) \| IQ3_XS \| 3.1 \| \|
	\| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_014-GGUF/resolve/main/LCARS_AI_014.Q3_K_S.gguf) \| Q3_K_S \| 3.3 \| \|
	\| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_014-GGUF/resolve/main/LCARS_AI_014.IQ3_S.gguf) \| IQ3_S \| 3.3 \| beats Q3_K* \|
	\| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_014-GGUF/resolve/main/LCARS_AI_014.IQ3_M.gguf) \| IQ3_M \| 3.4 \| \|
	\| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_014-GGUF/resolve/main/LCARS_AI_014.Q3_K_M.gguf) \| Q3_K_M \| 3.6 \| lower quality \|
	\| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_014-GGUF/resolve/main/LCARS_AI_014.Q3_K_L.gguf) \| Q3_K_L \| 3.9 \| \|
	\| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_014-GGUF/resolve/main/LCARS_AI_014.IQ4_XS.gguf) \| IQ4_XS \| 4.0 \| \|
	\| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_014-GGUF/resolve/main/LCARS_AI_014.Q4_K_S.gguf) \| Q4_K_S \| 4.2 \| fast, recommended \|
	\| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_014-GGUF/resolve/main/LCARS_AI_014.Q4_K_M.gguf) \| Q4_K_M \| 4.5 \| fast, recommended \|
	\| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_014-GGUF/resolve/main/LCARS_AI_014.Q5_K_S.gguf) \| Q5_K_S \| 5.1 \| \|
	\| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_014-GGUF/resolve/main/LCARS_AI_014.Q5_K_M.gguf) \| Q5_K_M \| 5.2 \| \|
	\| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_014-GGUF/resolve/main/LCARS_AI_014.Q6_K.gguf) \| Q6_K \| 6.0 \| very good quality \|
	\| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_014-GGUF/resolve/main/LCARS_AI_014.Q8_0.gguf) \| Q8_0 \| 7.8 \| fast, best quality \|
	\| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_014-GGUF/resolve/main/LCARS_AI_014.f16.gguf) \| f16 \| 14.6 \| 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.

	<!-- end -->