base_model: PJMixers-Dev/Gemma-3-Earthen-v0.2-4B
datasets:
- BeaverAI/REDACTED1
- BeaverAI/REDACTED2
- BeaverAI/REDACTED3
- BeaverAI/REDACTED4
- PJMixers-Dev/Lit-axo-Shuffled
- PJMixers-Dev/Mielikki_Erebus-87k-axo
- PJMixers/RyokoAI_Honeyfeed3600-Cleanish
- PJMixers-Dev/allura-org_fujin-cleaned-stage-2-axo
- Nelathan/synthetic-sugar-quill
- PJMixers-Dev/winglian_visual-novels-json-axo
- PJMixers-Dev/recursal_SCP-RECURSAL-Cleaned
- PJMixers-Dev/Subtitles
- PJMixers-Dev/KaraKaraWitch_AnimeSubtitle-axo
- PJMixers-Dev/Fundus-105K-Formatted
- PJMixers-Dev/Fundus-AP-News-Formatted
- PJMixers/AP-News-2024
- PJMixers-Dev/goodwiki-2024-12-04-axo
- epfl-llm/guidelines
- PJMixers-Dev/Gryphe-Aesir-RPG-Charcards-Opus-Mixed
- allura-org/gryphe-sonnet-3.5-charcards-names-added
- anthracite-org/c2_logs_32k_llama3_qwen2_v1.3
- PJMixers-Dev/MinervaAI_Aesir-Preview-Anon
- PJMixers-Dev/lemonilia_LimaRP-Simple-CustomShareGPT-Shuffled
- Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
- PJMixers-Dev/NyxKrage_chub-logs-sharegpt-longest-CustomShareGPT
- PJMixers/OpenLeecher_Teatime_all_logs_longest-ShareGPT
- grimulkan/aicg-logs-augmented
- grimulkan/PIPPA-augmented-dedup
- PJMixers/grimulkan_bluemoon_Karen_cleaned-carded-formatted
- PJMixers/lodrick-the-lafted_OpusStories-ShareGPT
- Gryphe/ChatGPT-4o-Writing-Prompts
- Gryphe/Opus-WritingPrompts
- anthracite-org/nopm_claude_writing_fixed
- PJMixers-Dev/Tiefighter-13B-Fake-Distill-ShareGPT
- allura-org/fujin-instruct-v2
- PocketDoc/Dans-Prosemaxx-Adventure
- PocketDoc/Dans-Failuremaxx-Adventure-3
language:
- en
library_name: transformers
license: gemma
mradermacher:
readme_rev: 1
quantized_by: mradermacher
About
static quants of https://huggingface.co/PJMixers-Dev/Gemma-3-Earthen-v0.2-4B
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Gemma-3-Earthen-v0.2-4B-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 | mmproj-Q8_0 | 0.7 | multi-modal supplement |
| GGUF | mmproj-f16 | 1.0 | multi-modal supplement |
| GGUF | Q2_K | 1.8 | |
| GGUF | Q3_K_S | 2.0 | |
| GGUF | Q3_K_M | 2.2 | lower quality |
| GGUF | Q3_K_L | 2.3 | |
| GGUF | IQ4_XS | 2.4 | |
| GGUF | Q4_K_S | 2.5 | fast, recommended |
| GGUF | Q4_K_M | 2.6 | fast, recommended |
| GGUF | Q5_K_S | 2.9 | |
| GGUF | Q5_K_M | 2.9 | |
| GGUF | Q6_K | 3.3 | very good quality |
| GGUF | Q8_0 | 4.2 | fast, best quality |
| GGUF | f16 | 7.9 | 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.