164 lines
6.6 KiB
Markdown
164 lines
6.6 KiB
Markdown
---
|
|
base_model: LeroyDyer/LCARS_AI_001
|
|
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
|
|
- tw
|
|
- es
|
|
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: nicoboss -->
|
|
weighted/imatrix quants of https://huggingface.co/LeroyDyer/LCARS_AI_001
|
|
|
|
<!-- provided-files -->
|
|
static quants are available at https://huggingface.co/mradermacher/LCARS_AI_001-GGUF
|
|
## 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_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-IQ1_S.gguf) | i1-IQ1_S | 1.7 | for the desperate |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-IQ1_M.gguf) | i1-IQ1_M | 1.9 | mostly desperate |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.1 | |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.3 | |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-IQ2_S.gguf) | i1-IQ2_S | 2.4 | |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-IQ2_M.gguf) | i1-IQ2_M | 2.6 | |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-Q2_K.gguf) | i1-Q2_K | 2.8 | IQ3_XXS probably better |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 2.9 | lower quality |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-IQ3_XS.gguf) | i1-IQ3_XS | 3.1 | |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.3 | IQ3_XS probably better |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-IQ3_S.gguf) | i1-IQ3_S | 3.3 | beats Q3_K* |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-IQ3_M.gguf) | i1-IQ3_M | 3.4 | |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-Q3_K_M.gguf) | i1-Q3_K_M | 3.6 | IQ3_S probably better |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-Q3_K_L.gguf) | i1-Q3_K_L | 3.9 | IQ3_M probably better |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-IQ4_XS.gguf) | i1-IQ4_XS | 4.0 | |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-Q4_0.gguf) | i1-Q4_0 | 4.2 | fast, low quality |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.2 | optimal size/speed/quality |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-Q4_K_M.gguf) | i1-Q4_K_M | 4.5 | fast, recommended |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-Q5_K_S.gguf) | i1-Q5_K_S | 5.1 | |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-Q5_K_M.gguf) | i1-Q5_K_M | 5.2 | |
|
|
| [GGUF](https://huggingface.co/mradermacher/LCARS_AI_001-i1-GGUF/resolve/main/LCARS_AI_001.i1-Q6_K.gguf) | i1-Q6_K | 6.0 | practically like static Q6_K |
|
|
|
|
Here is a handy graph by ikawrakow comparing some lower-quality quant
|
|
types (lower is better):
|
|
|
|
|
|
|
|
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. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.
|
|
|
|
<!-- end -->
|