LLM EXPLORER 56,604 MODELS INDEXED

G4 MeroMero V2 31B Heretic ARA LoRA by kabachuha

By kabachuha · 0 downloads

G4 MeroMero V2 31B Heretic ARA LoRA is an open-source language model by kabachuha. Features: 31b LLM, VRAM: 0.6GB, License: apache-2.0.

  Abliterated   Ara   Ara-lora Base model:adapter:zerofata/g4... Base model:zerofata/g4-meromer...   Conversational   Decensored   Endpoints compatible   Gemma4   Heretic   Image-text-to-text   Lora   Meromero   Region:us   Roleplay   Safetensors   Uncensored

G4 MeroMero V2 31B Heretic ARA LoRA Parameters and Internals

LLM NameG4 MeroMero V2 31B Heretic ARA LoRA
Repository πŸ€—https://huggingface.co/kabachuha/G4-MeroMero-v2-31B-Heretic-ARA-LoRA 
Base Model(s)  G4 MeroMero V2 31B   zerofata/G4-MeroMero-v2-31B
Model Size31b
Required VRAM0.6 GB
Updated2026-08-09
Maintainerkabachuha
Model Files  0.6 GB
Model ArchitectureAutoModel
Licenseapache-2.0
Is Biasednone
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesmodel.language_model.layers.6.mlp.down_proj|model.language_model.layers.41.mlp.down_proj|model.language_model.layers.20.self_attn.o_proj|model.language_model.layers.44.mlp.down_proj|model.language_model.layers.22.mlp.down_proj|model.language_model.layers.50.mlp.down_proj|model.language_model.layers.31.self_attn.o_proj|model.language_model.layers.0.mlp.down_proj|model.language_model.layers.29.mlp.down_proj|model.language_model.layers.33.mlp.down_proj|model.language_model.layers.23.mlp.down_proj|model.language_model.layers.32.mlp.down_proj|model.language_model.layers.36.mlp.down_proj|model.language_model.layers.16.self_attn.o_proj|model.language_model.layers.32.self_attn.o_proj|model.language_model.layers.14.mlp.down_proj|model.language_model.layers.9.mlp.down_proj|model.language_model.layers.48.self_attn.o_proj|model.language_model.layers.17.self_attn.o_proj|model.language_model.layers.37.self_attn.o_proj|model.language_model.layers.45.mlp.down_proj|model.language_model.layers.42.self_attn.o_proj|model.language_model.layers.24.mlp.down_proj|model.language_model.layers.7.self_attn.o_proj|model.language_model.layers.37.mlp.down_proj|model.language_model.layers.20.mlp.down_proj|model.language_model.layers.49.self_attn.o_proj|model.language_model.layers.41.self_attn.o_proj|model.language_model.layers.33.self_attn.o_proj|model.language_model.layers.43.mlp.down_proj|model.language_model.layers.1.self_attn.o_proj|model.language_model.layers.19.self_attn.o_proj|model.language_model.layers.39.mlp.down_proj|model.language_model.layers.31.mlp.down_proj|model.language_model.layers.27.mlp.down_proj|model.language_model.layers.15.mlp.down_proj|model.language_model.layers.45.self_attn.o_proj|model.language_model.layers.55.mlp.down_proj|model.language_model.layers.4.mlp.down_proj|model.language_model.layers.34.mlp.down_proj|model.language_model.layers.2.mlp.down_proj|model.language_model.layers.4.self_attn.o_proj|model.language_model.layers.12.mlp.down_proj|model.language_model.layers.26.mlp.down_proj|model.language_model.layers.14.self_attn.o_proj|model.language_model.layers.24.self_attn.o_proj|model.language_model.layers.47.self_attn.o_proj|model.language_model.layers.53.self_attn.o_proj|model.language_model.layers.58.mlp.down_proj|model.language_model.layers.59.mlp.down_proj|model.language_model.layers.59.self_attn.o_proj|model.language_model.layers.19.mlp.down_proj|model.language_model.layers.30.self_attn.o_proj|model.language_model.layers.47.mlp.down_proj|model.language_model.layers.49.mlp.down_proj|model.language_model.layers.53.mlp.down_proj|model.language_model.layers.30.mlp.down_proj|model.language_model.layers.10.mlp.down_proj|model.language_model.layers.39.self_attn.o_proj|model.language_model.layers.12.self_attn.o_proj|model.language_model.layers.35.mlp.down_proj|model.language_model.layers.8.self_attn.o_proj|model.language_model.layers.16.mlp.down_proj|model.language_model.layers.21.self_attn.o_proj|model.language_model.layers.48.mlp.down_proj|model.language_model.layers.46.self_attn.o_proj|model.language_model.layers.38.mlp.down_proj|model.language_model.layers.42.mlp.down_proj|model.language_model.layers.40.self_attn.o_proj|model.language_model.layers.6.self_attn.o_proj|model.language_model.layers.50.self_attn.o_proj|model.language_model.layers.55.self_attn.o_proj|model.language_model.layers.18.self_attn.o_proj|model.language_model.layers.13.self_attn.o_proj|model.language_model.layers.54.mlp.down_proj|model.language_model.layers.5.mlp.down_proj|model.language_model.layers.57.mlp.down_proj|model.language_model.layers.34.self_attn.o_proj|model.language_model.layers.10.self_attn.o_proj|model.language_model.layers.58.self_attn.o_proj|model.language_model.layers.35.self_attn.o_proj|model.language_model.layers.1.mlp.down_proj|model.language_model.layers.56.self_attn.o_proj|model.language_model.layers.25.mlp.down_proj|model.language_model.layers.29.self_attn.o_proj|model.language_model.layers.51.self_attn.o_proj|model.language_model.layers.18.mlp.down_proj|model.language_model.layers.43.self_attn.o_proj|model.language_model.layers.11.self_attn.o_proj|model.language_model.layers.57.self_attn.o_proj|model.language_model.layers.0.self_attn.o_proj|model.language_model.layers.38.self_attn.o_proj|model.language_model.layers.40.mlp.down_proj|model.language_model.layers.2.self_attn.o_proj|model.language_model.layers.26.self_attn.o_proj|model.language_model.layers.51.mlp.down_proj|model.language_model.layers.52.mlp.down_proj|model.language_model.layers.9.self_attn.o_proj|model.language_model.layers.13.mlp.down_proj|model.language_model.layers.56.mlp.down_proj|model.language_model.layers.3.mlp.down_proj|model.language_model.layers.8.mlp.down_proj|model.language_model.layers.23.self_attn.o_proj|model.language_model.layers.7.mlp.down_proj|model.language_model.layers.15.self_attn.o_proj|model.language_model.layers.27.self_attn.o_proj|model.language_model.layers.25.self_attn.o_proj|model.language_model.layers.21.mlp.down_proj|model.language_model.layers.52.self_attn.o_proj|model.language_model.layers.22.self_attn.o_proj|model.language_model.layers.28.mlp.down_proj|model.language_model.layers.28.self_attn.o_proj|model.language_model.layers.5.self_attn.o_proj|model.language_model.layers.36.self_attn.o_proj|model.language_model.layers.46.mlp.down_proj|model.language_model.layers.3.self_attn.o_proj|model.language_model.layers.11.mlp.down_proj|model.language_model.layers.44.self_attn.o_proj|model.language_model.layers.54.self_attn.o_proj|model.language_model.layers.17.mlp.down_proj
LoRA Alpha64
LoRA Dropout0
R Param64

Best Alternatives to G4 MeroMero V2 31B Heretic ARA LoRA

Best Alternatives
Context / RAM
Downloads
Likes
OTel 2.0 LLM 31B IT256K / 64.2 GB40070149
Gemma 4 31B Glimmer Rp V0.20K / 0.5 GB190
Gemma 4 31B Vore Lora0K / 0 GB470
...31B It Distill Qwen3 0.6B Lora0K / 0 GB50
Couture Engine 31B V1.0 Lora0K / 0.5 GB230
Note: green Score (e.g. "73.2") means that the model is better than kabachuha/G4-MeroMero-v2-31B-Heretic-ARA-LoRA.