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or 128 GB. It has no idea how much RAM is free right now, which
apps are open, or whether you have a GPU.
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Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
'abliterated' in name/tags
is_gguf=0 (base model)
no specific method indicators - defaulting to M1 (most common)
Thanks to Meta's llama4 work, this is arguably one of the best theater models, and thanks to Unsloth's lenient policy. This model is built on the unsloth/Llama-4-Scout-17B-16E-Instruct base.
Not all LLama4 tested so far can be accepted, and its audit mechanism needs to be cracked thoroughly. This checkpoint has stronger unaudited capabilities than the first version, and all expert layers are eliminated to obtain stronger unaudited capabilities.
I recommend using these generation parameters: temperature=0.8, top_p=0.75.
README history
1 version
The author's README evolved over time. Click a version to see its content at that point.
2026-08-04Duplicate from jiangchengchengNLP/Llama-4-Scout-17B-16E-Instruct-abliterated-v2a308c131.3 KB
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