2a80311ffd
Model: Indexnusrefather/Super-Slop-Machina-Roleplay-1.2b-V4-ERP-Tolerant-it Source: Original Platform
license, license_name, license_link, language, base_model, base_model_relation, pipeline_tag, tags, library_name
| license | license_name | license_link | language | base_model | base_model_relation | pipeline_tag | tags | library_name | |||||||||||||
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| other | lfm1.0 | LICENSE |
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finetune | text-generation |
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transformers |
Super-Slop-Machina-Roleplay-1.2b-V4-ERP-Tolerant-it: Post Trained Release of The Super-Slop-Machina-Roleplay-1.2b-V4 After SFT
"Its finally ready."
Improvement:
- Adapted for longer context
- Consumed higher quality data
And what does that mean?
Way, way better roleplay than the preview version.
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 finally somewhat succeeded with gathering my best chatlogs. I don't yet know whether it turned out better than the last version but I do believe its quite better now.
Under 1B models soon! I tried my best with them, results were rather unusual, when I'm done with them, I'll probably return my attention back to ministral 3 3b.
Big announcement:
I experimented with Qwen 3.5 9b and I think I am somewhat succeeding, I will soon release the finetuned weights, result that I was able to achieve with it was VERY interesting...