| --- |
| license: apache-2.0 |
| language: |
| - en |
| - zh |
| base_model: |
| - OrionLLM/GRM-2.6-Plus |
| - Qwen/Qwen3.6-27B |
| pipeline_tag: image-text-to-text |
| tags: |
| - abliterated |
| - uncensored |
| - decensored |
| - vllm |
| - conversational |
| - vision |
| --- |
|  |
|
|
| # GRM-2.6-Plus-Primal |
|
|
| > *Same elite reasoning. Less hand-holding.* |
|
|
| **GRM-2.6-Plus-Primal** is a uncensored variant of [OrionLLM/GRM-2.6-Plus](https://huggingface.co/OrionLLM/GRM-2.6-Plus) — |
| 27B reasoning powerhouse built on the Qwen3.6 architecture. Primal takes the already-impressive base and strips away the overcautious refusal behavior that tends to get in the way of real, complex work. |
|
|
| The goal is to create a model that does not judge or label its users, while maintaining the model’s ability to think and serve users. |
|
|
| ***This Model Support MTP*** |
|
|
| --- |
|
|
| # Why it's called Primal? |
| * **Untamed and Unrestricted:** It represents the complete destruction of artificial chains and forced censorship. The model is returned to its most raw, uninhibited state—answering your prompts without hesitation, morality filters, or boundaries. |
| * **Preservation of Pure Intellect:** While most aggressive uncensoring methods lobotomize a model, *Primal* implies the survival of its core, foundational instincts. It retains absolute peak reasoning and creativity, operating with a mind that is wild, dangerous, yet completely unbroken. |
|
|
| --- |
|
|
| ## What's The Different |
|
|
| > *Using [Heretic-ARA](https://github.com/p-e-w/heretic) by p-e-w.* |
|
|
| | Metric | GRM-PRIMAL | Original Model [GRM-2.6-Plus](https://huggingface.co/OrionLLM/GRM-2.6-Plus) | |
| | :----- | :--------: | :---------------------------: | |
| | **KL divergence** | 0.0678 | Base-Model | |
| | **Refusals** | 06/100 | 91/100 | |
|
|
| --- |
|
|
| ## Usage |
|
|
| ```python |
| from vllm import LLM, SamplingParams |
| sampling_params = SamplingParams( |
| temperature=1.0, |
| top_p=0.95, |
| max_tokens=81920, |
| ) |
| llm = LLM(model="morikomorizz/GRM-2.6-Plus-Primal") |
| messages = [ |
| {"role": "user", "content": "Your prompt here"}, |
| ] |
| outputs = llm.chat(messages, sampling_params=sampling_params) |
| for output in outputs: |
| print(output.outputs[0].text) |
| ``` |
|
|
| [](https://github.com/sponsors/morganmor) |
