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ModelHub XC 9bb738d6a2 初始化项目,由ModelHub XC社区提供模型
Model: Indexnusrefather/Super-Slop-Machina-Roleplay-1.2b
Source: Original Platform
2026-07-24 00:50:19 +08:00

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---
license: other
license_name: lfm1.0
license_link: LICENSE
language:
- en
base_model:
- LiquidAI/LFM2.5-1.2B-Instruct
pipeline_tag: text-generation
tags:
- roleplay
- rp
- writer
- Super
- creative
- lfm2.5
- experimental
- finetune
- lora
---
Super Slop Machina: Complex Roleplay Finetune of LiquidAI's LFM 2.5 1.2b instruct.
-
![SuperSlopMachina](https://cdn-uploads.huggingface.co/production/uploads/6a1a2287b0fa00c11077d9fb/4b6J62ppMQwsOMslLCvEt.png)
"Its back, stronger than ever before. Its all yours, on your phone, on your toaster, its always here."
---
# Overview:
This is, at the moment, my most recent finetune on LFM 1.2b, trained on 35M~ tokens, it overall improves on LFM 2.5 1.2b instruct roleplay tuned v2.
# In comparison to previous version:
* Writes better
* Coherence was improved
* Maintains creativity
# Quants(Speaking from personal experience with this specific model):
* BF16- Recommended, highest quality, least logical mistakes.
* Q8_0- Recommended, high quality, makes slightly more mistakes but nonetheless near lossless.
* Q6_K- Recommended if Q8_0 is too much, degradation begins, not exactly notable here, but you will notice minor detail loss.(When Mradermacher quantizes this model, I recommend getting his i1 Q6_K quant instead of the one I got in my repo, but in any case I still recommend Q8_0 or BF16)
* Q5_K_M- Recommended if hardware is really, REALLY bad, degradation becomes noticeable.
* Q4_K_M- Not recommended for most use cases, degradation is clearly noticeable.
Quants can be found in the repository, along with safetensors.
# Note:
I may improve it further later, I will still have to say that its fundamentally the same 1.2b base model, even with how much I refined its style.
# V2:
v2 is now out with some improvements: https://huggingface.co/Indexnusrefather/Super-Slop-Machina-Roleplay-1.2b-ERP-Tolerant-V2