base_model: PocketDoc/Dans-PersonalityEngine-v1.0.0-8b
datasets:
- PocketDoc/Dans-MemoryCore-CoreCurriculum-Small
- PocketDoc/Dans-Prosemaxx-Gutenberg
- PocketDoc/Dans-Prosemaxx-Cowriter-S
- PocketDoc/Dans-Prosemaxx-Adventure
- PocketDoc/Dans-Prosemaxx-Opus-Writing
- PocketDoc/Dans-Assistantmaxx-Sharegpt
- PocketDoc/Dans-Assistantmaxx-OpenAssistant2
- PocketDoc/Dans-Assistantmaxx-Opus-instruct-1
- PocketDoc/Dans-Assistantmaxx-Opus-instruct-2
- PocketDoc/Dans-Assistantmaxx-Opus-instruct-3
- PocketDoc/Dans-Assistantmaxx-Opus-Multi-Instruct
- PocketDoc/Dans-Assistantmaxx-sonnetorca-subset
- PocketDoc/Dans-Assistantmaxx-NoRobots
- AquaV/Energetic-Materials-Sharegpt
- AquaV/Chemical-Biological-Safety-Applications-Sharegpt
- AquaV/US-Army-Survival-Sharegpt
- AquaV/Resistance-Sharegpt
- AquaV/Interrogation-Sharegpt
- AquaV/Multi-Environment-Operations-Sharegpt
- PocketDoc/Dans-Mathmaxx
- PJMixers/Math-Multiturn-1K-ShareGPT
- PocketDoc/Dans-Benchmaxx
- PocketDoc/Dans-Codemaxx-LeetCode
- PocketDoc/Dans-Codemaxx-CodeFeedback-Conversations
- PocketDoc/Dans-Codemaxx-CodeFeedback-SingleTurn
- PocketDoc/Dans-Taskmaxx
- PocketDoc/Dans-Taskmaxx-DataPrepper
- PocketDoc/Dans-Taskmaxx-ConcurrentQA-Reworked
- PocketDoc/Dans-Systemmaxx
- PocketDoc/Dans-Toolmaxx-Agent
- PocketDoc/Dans-Toolmaxx-ShellCommands
- PocketDoc/Dans-ASCIIMaxx-Wordart
- PocketDoc/Dans-Personamaxx
- PocketDoc/DansTestYard
- PocketDoc/Dans-Logicmaxx-Skunkworks
language:
- en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
- chemistry
- biology
- code
- climate
- text-generation-inference
About
static quants of https://huggingface.co/PocketDoc/Dans-PersonalityEngine-v1.0.0-8b
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Dans-PersonalityEngine-v1.0.0-8b-i1-GGUF
Usage
If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs 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 | Q2_K | 3.3 | |
| GGUF | Q3_K_S | 3.8 | |
| GGUF | Q3_K_M | 4.1 | lower quality |
| GGUF | Q3_K_L | 4.4 | |
| GGUF | IQ4_XS | 4.6 | |
| GGUF | Q4_0_4_4 | 4.8 | fast on arm, low quality |
| GGUF | Q4_K_S | 4.8 | fast, recommended |
| GGUF | Q4_K_M | 5.0 | fast, recommended |
| GGUF | Q5_K_S | 5.7 | |
| GGUF | Q5_K_M | 5.8 | |
| GGUF | Q6_K | 6.7 | very good quality |
| GGUF | Q8_0 | 8.6 | fast, best quality |
| GGUF | f16 | 16.2 | 16 bpw, overkill |
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, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.