base_model: Novaciano/HarmfulProject-3.2-1B
datasets:
- mlabonne/FineTome-100k
- microsoft/orca-math-word-problems-200k
- m-a-p/CodeFeedback-Filtered-Instruction
- cognitivecomputations/dolphin-coder
- PawanKrd/math-gpt-4o-200k
- V3N0M/Jenna-50K-Alpaca-Uncensored
- FreedomIntelligence/medical-o1-reasoning-SFT
language: - es
- en
library_name: transformers
quantized_by: mradermacher
tags: - llama3.2
- llama
- mergekit
- merge
- llama-cpp
- nsfw
- uncensored
- abliterated
- 1b
- 4-bit
- not-for-all-audiences
About
static quants of https://huggingface.co/Novaciano/HarmfulProject-3.2-1B
weighted/imatrix quants are available at https://huggingface.co/mradermacher/UNCENSORED-HarmfulProject-3.2-1B-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 | 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.