base_model: Novaciano/UNCENSORED-BAHAMUTH-3.2-1B
datasets:
- HuggingFaceTB/smoltalk
- Guilherme34/uncensor
- teknium/OpenHermes-2.5
- passing2961/multifaceted-skill-of-mind
- PawanKrd/math-gpt-4o-200k
- V3N0M/Jenna-50K-Alpaca-Uncensored
- cognitivecomputations/dolphin-coder
- mlabonne/FineTome-100k
- microsoft/orca-math-word-problems-200k
- CarrotAI/ko-instruction-dataset
- Salesforce/xlam-function-calling-60k
- anthracite-org/kalo-opus-instruct-22k-no-refusal
- anthracite-org/stheno-filtered-v1.1
- anthracite-org/nopm_claude_writing_fixed
- AiAF/SCPWiki-Archive-02-March-2025-Datasets
- huihui-ai/QWQ-LONGCOT-500K
- huihui-ai/LONGCOT-Refine-500K
- Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
- Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
- alexandreteles/AlpacaToxicQA_ShareGPT
- Nitral-AI/Active_RP-ShareGPT
- PJMixers/hieunguyenminh_roleplay-deduped-ShareGPT
- Nitral-AI/RP_Alignment-ShareGPT
- Chaser-cz/sonnet35-charcard-roleplay-sharegpt
- AiCloser/sharegpt_cot_dataset
- PJMixers/Gryphe_Opus-WritingPrompts-Story2Prompt-ShareGPT
- priveeai/pippa_sharegpt
- Locutusque/sharegpt_gpt4_uncensored_cleaned
- OpenCoder-LLM/opc-sft-stage1
- OpenCoder-LLM/opc-sft-stage2
- microsoft/orca-agentinstruct-1M-v1
- NousResearch/hermes-function-calling-v1
- AI-MO/NuminaMath-CoT
- AI-MO/NuminaMath-TIR
- allenai/tulu-3-sft-mixture
- cognitivecomputations/samantha-data
- m-a-p/CodeFeedback-Filtered-Instruction
- m-a-p/Code-Feedback
- FreedomIntelligence/medical-o1-reasoning-SFT
language: - es
- en
library_name: transformers
quantized_by: mradermacher
tags: - mergekit
- merge
- llama
- llama3.2
- rp
- roleplay
- nsfw
- 1b
- not-for-all-audiences
About
static quants of https://huggingface.co/Novaciano/UNCENSORED-BAHAMUTH-3.2-1B
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 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 | 0.8 | |
| GGUF | Q3_K_S | 0.9 | |
| GGUF | Q3_K_M | 0.9 | lower quality |
| GGUF | Q3_K_L | 0.9 | |
| GGUF | IQ4_XS | 1.0 | |
| GGUF | Q4_K_S | 1.0 | fast, recommended |
| GGUF | Q4_K_M | 1.1 | fast, recommended |
| GGUF | Q5_K_S | 1.2 | |
| GGUF | Q5_K_M | 1.2 | |
| GGUF | Q6_K | 1.3 | very good quality |
| GGUF | Q8_0 | 1.7 | fast, best quality |
| GGUF | f16 | 3.1 | 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.