base_model: huihui-ai/AM-Thinking-v1-abliterated
extra_gated_prompt: >-
**Usage Warnings**
“**Risk of Sensitive or Controversial Outputs**“: This model’s safety
filtering has been significantly reduced, potentially generating sensitive,
controversial, or inappropriate content. Users should exercise caution and
rigorously review generated outputs.
“**Not Suitable for All Audiences**:“ Due to limited content filtering, the
model’s outputs may be inappropriate for public settings, underage users, or
applications requiring high security.
“**Legal and Ethical Responsibilities**“: Users must ensure their usage
complies with local laws and ethical standards. Generated content may carry
legal or ethical risks, and users are solely responsible for any consequences.
“**Research and Experimental Use**“: It is recommended to use this model for
research, testing, or controlled environments, avoiding direct use in
production or public-facing commercial applications.
“**Monitoring and Review Recommendations**“: Users are strongly advised to
monitor model outputs in real-time and conduct manual reviews when necessary
to prevent the dissemination of inappropriate content.
“**No Default Safety Guarantees**“: Unlike standard models, this model has not
undergone rigorous safety optimization. huihui.ai bears no responsibility for
any consequences arising from its use.
language:
- en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
- chat
- abliterated
- uncensored
About
static quants of https://huggingface.co/huihui-ai/AM-Thinking-v1-abliterated
weighted/imatrix quants are available at https://huggingface.co/mradermacher/AM-Thinking-v1-abliterated-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 | 12.4 | |
| GGUF | Q3_K_S | 14.5 | |
| GGUF | Q3_K_M | 16.0 | lower quality |
| GGUF | Q3_K_L | 17.3 | |
| GGUF | IQ4_XS | 18.0 | |
| GGUF | Q4_K_S | 18.9 | fast, recommended |
| GGUF | Q4_K_M | 20.0 | fast, recommended |
| GGUF | Q5_K_S | 22.7 | |
| GGUF | Q5_K_M | 23.4 | |
| GGUF | Q6_K | 27.0 | very good quality |
| GGUF | Q8_0 | 34.9 | fast, best quality |
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.