MiniMax H3 Prompt Rewriter LoRA Omni is an open-source language model by lightx2v. Features: 7b LLM, VRAM: 1.3GB, License: other, LLM Explorer Score: 0.37.
| LLM Name | MiniMax H3 Prompt Rewriter LoRA Omni |
| Repository 🤗 | https://huggingface.co/lightx2v/MiniMax-H3-Prompt-Rewriter-LoRA-Omni |
| Base Model(s) | |
| Model Size | 7b |
| Required VRAM | 1.3 GB |
| Updated | 2026-08-27 |
| Maintainer | lightx2v |
| Model Files | |
| Supported Languages | en zh |
| Model Architecture | Adapter |
| License | other |
| Is Biased | none |
| PEFT Type | LORA |
| LoRA Model | Yes |
| PEFT Target Modules | model.layers.22.self_attn.k_proj|layers.6.mlp.up_proj|model.layers.18.self_attn.k_proj|layers.24.mlp.gate_proj|model.layers.5.self_attn.k_proj|model.layers.9.self_attn.q_proj|layers.19.mlp.up_proj|layers.0.mlp.gate_proj|layers.21.mlp.up_proj|model.layers.3.self_attn.q_proj|layers.9.mlp.gate_proj|layers.14.mlp.down_proj|model.layers.11.self_attn.k_proj|model.layers.12.self_attn.k_proj|model.layers.12.self_attn.q_proj|model.layers.21.self_attn.k_proj|model.layers.2.self_attn.k_proj|layers.22.mlp.gate_proj|layers.13.mlp.down_proj|layers.7.mlp.gate_proj|layers.23.mlp.up_proj|layers.19.mlp.gate_proj|model.layers.22.self_attn.q_proj|layers.4.mlp.up_proj|model.layers.21.self_attn.v_proj|layers.25.mlp.gate_proj|model.layers.15.self_attn.k_proj|model.layers.7.self_attn.k_proj|model.layers.8.self_attn.v_proj|model.layers.26.self_attn.v_proj|model.layers.23.self_attn.v_proj|layers.4.mlp.down_proj|layers.8.mlp.down_proj|layers.10.mlp.up_proj|layers.24.mlp.down_proj|model.layers.14.self_attn.k_proj|model.layers.16.self_attn.k_proj|layers.8.mlp.up_proj|layers.0.mlp.up_proj|layers.18.mlp.gate_proj|model.layers.14.self_attn.q_proj|model.layers.12.self_attn.v_proj|model.layers.10.self_attn.k_proj|model.layers.17.self_attn.k_proj|layers.1.mlp.gate_proj|model.layers.26.self_attn.q_proj|layers.17.mlp.gate_proj|layers.11.mlp.up_proj|layers.15.mlp.gate_proj|model.layers.11.self_attn.q_proj|model.layers.20.self_attn.v_proj|model.layers.10.self_attn.v_proj|layers.15.mlp.up_proj|layers.1.mlp.up_proj|model.layers.16.self_attn.v_proj|model.layers.13.self_attn.v_proj|model.layers.25.self_attn.v_proj|model.layers.18.self_attn.v_proj|model.layers.15.self_attn.q_proj|layers.13.mlp.up_proj|model.layers.20.self_attn.q_proj|layers.20.mlp.down_proj|layers.5.mlp.up_proj|model.layers.19.self_attn.k_proj|layers.18.mlp.down_proj|layers.27.mlp.gate_proj|layers.3.mlp.up_proj|layers.9.mlp.down_proj|layers.14.mlp.up_proj|layers.8.mlp.gate_proj|model.layers.0.self_attn.q_proj|model.layers.18.self_attn.q_proj|model.layers.1.self_attn.q_proj|model.layers.24.self_attn.k_proj|layers.22.mlp.up_proj|model.layers.4.self_attn.q_proj|model.layers.0.self_attn.v_proj|model.layers.8.self_attn.q_proj|layers.17.mlp.up_proj|layers.1.mlp.down_proj|layers.6.mlp.down_proj|layers.10.mlp.down_proj|layers.16.mlp.up_proj|model.layers.3.self_attn.v_proj|model.layers.4.self_attn.k_proj|model.layers.23.self_attn.k_proj|model.layers.0.self_attn.k_proj|layers.7.mlp.up_proj|layers.20.mlp.up_proj|model.layers.6.self_attn.v_proj|layers.23.mlp.gate_proj|model.layers.27.self_attn.q_proj|layers.26.mlp.up_proj|layers.14.mlp.gate_proj|layers.21.mlp.down_proj|model.layers.19.self_attn.q_proj|model.layers.7.self_attn.q_proj|model.layers.7.self_attn.v_proj|layers.12.mlp.down_proj|layers.4.mlp.gate_proj|layers.27.mlp.down_proj|layers.23.mlp.down_proj|model.layers.13.self_attn.k_proj|layers.22.mlp.down_proj|model.layers.24.self_attn.q_proj|model.layers.25.self_attn.q_proj|model.layers.17.self_attn.v_proj|model.layers.20.self_attn.k_proj|layers.5.mlp.down_proj|model.layers.23.self_attn.q_proj|layers.16.mlp.gate_proj|layers.26.mlp.down_proj|layers.12.mlp.up_proj|model.layers.4.self_attn.v_proj|layers.13.mlp.gate_proj|model.layers.3.self_attn.k_proj|layers.17.mlp.down_proj|model.layers.10.self_attn.q_proj|layers.21.mlp.gate_proj|model.layers.14.self_attn.v_proj|layers.2.mlp.up_proj|layers.19.mlp.down_proj|layers.25.mlp.up_proj|layers.7.mlp.down_proj|layers.12.mlp.gate_proj|layers.20.mlp.gate_proj|model.layers.16.self_attn.q_proj|layers.25.mlp.down_proj|layers.3.mlp.gate_proj|layers.5.mlp.gate_proj|model.layers.26.self_attn.k_proj|o_proj|layers.24.mlp.up_proj|layers.0.mlp.down_proj|layers.9.mlp.up_proj|model.layers.1.self_attn.v_proj|model.layers.25.self_attn.k_proj|model.layers.6.self_attn.q_proj|layers.10.mlp.gate_proj|model.layers.24.self_attn.v_proj|layers.2.mlp.gate_proj|model.layers.2.self_attn.v_proj|model.layers.8.self_attn.k_proj|layers.18.mlp.up_proj|model.layers.2.self_attn.q_proj|layers.26.mlp.gate_proj|model.layers.27.self_attn.k_proj|model.layers.13.self_attn.q_proj|layers.11.mlp.down_proj|model.layers.21.self_attn.q_proj|model.layers.15.self_attn.v_proj|model.layers.22.self_attn.v_proj|layers.27.mlp.up_proj|layers.15.mlp.down_proj|layers.6.mlp.gate_proj|model.layers.17.self_attn.q_proj|model.layers.9.self_attn.v_proj|layers.2.mlp.down_proj|layers.16.mlp.down_proj|model.layers.27.self_attn.v_proj|model.layers.5.self_attn.v_proj|model.layers.11.self_attn.v_proj|model.layers.6.self_attn.k_proj|model.layers.5.self_attn.q_proj|model.layers.19.self_attn.v_proj|layers.11.mlp.gate_proj|model.layers.9.self_attn.k_proj|model.layers.1.self_attn.k_proj|layers.3.mlp.down_proj |
| LoRA Alpha | 128 |
| LoRA Dropout | 0.1 |
| R Param | 128 |
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| Qwen Megumin | 0K / 0.1 GB | 11 | 1 |
| Mistral 7B Instruct Vi Alpaca | 0K / 0.4 GB | 5 | 0 |
| ...s 25 Mistral 7B Irca DPO Pairs | 0K / 0.1 GB | 6 | 0 |
| Qwen1.5 7B Chat Sa V0.1 | 0K / 0 GB | 8 | 0 |
| Uk Fraud Chatbot Llama2 | 0K / 0.4 GB | 6 | 0 |
| Zephyr 7B Ipo 0K 15K I1 | 0K / 0.7 GB | 5 | 0 |
| Deepseek Llm 7B Chat Sa V0.1 | 0K / 0 GB | 7 | 0 |
| Hr Other 7B Lora | 0K / 0.2 GB | 30 | 0 |
| Mistral 7B Instruct Sa V0.1 | 0K / 0 GB | 9 | 0 |
| Deepthink Reasoning Adapter | 0K / 0.2 GB | 16 | 3 |