license, language, base_model, pipeline_tag, library_name, tags
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| apache-2.0 |
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text-generation | transformers |
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Qwen3-4B-Element4-Eva
This is a model merge between Qwen3-4B-Element4 and FutureMa/Eva-4B.
Brainwaves of qx86-hi quants of the parent models
Element4 0.582,0.779,0.849,0.708,0.442,0.771,0.655
Eva-4B 0.539,0.747,0.864,0.606,0.412,0.751,0.605
Eva merged models
Agent-Eva 0.568,0.775,0.872,0.699,0.418,0.777,0.654
Element8-Eva 0.559,0.768,0.872,0.694,0.422,0.765,0.647
Element4-Eva
bf16 0.570,0.781,0.869,0.689,0.422,0.769,0.645
qx86-hi 0.567,0.781,0.868,0.689,0.426,0.773,0.642
qx64-hi 0.567,0.772,0.865,0.679,0.424,0.772,0.641
mxfp4 0.549,0.757,0.864,0.666,0.414,0.764,0.635
Element4 is a merge of Qwen3-4B-Engineer3x and Qwen3-4B-Agent, and serves as a base for the higher number elements. The Agent is Heretic-abliterated, which provides for some interesting friction in the model chains of thought, that only enhances the inference with some original AI humour.
The qx86-hi quant performs at the same level with full precision in this model.
The Element models are profiled to act as agents on the Star Trek DS9 station, in a roleplay scenario.
The models can be used for regular tasks as well.
Each comes with different skills. I found FutureMa/Eva-4B recently with an interesting model card:
Eva-4B is a 4B-parameter model for detecting evasive answers in earnings call Q&A.
In Element8-Eva, that would be Quark. Element8 is a very rich merge, with lower metrics than Agent.
Like I mentioned on the Element8-Eva model card, the FutureMa/Eva-4B was simply included for conversational skills.
-G