README.md

---
tags:
- merge
- mergekit
- lazymergekit
- UsernameJustAnother/Nemo-12B-Marlin-v5
- anthracite-org/magnum-12b-v2
base_model:
- UsernameJustAnother/Nemo-12B-Marlin-v5
- anthracite-org/magnum-12b-v2
model-index:
- name: MagnusIntellectus-12B-v1
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: IFEval (0-Shot)
      type: HuggingFaceH4/ifeval
      args:
        num_few_shot: 0
    metrics:
    - type: inst_level_strict_acc and prompt_level_strict_acc
      value: 44.21
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=GalrionSoftworks/MagnusIntellectus-12B-v1
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: BBH (3-Shot)
      type: BBH
      args:
        num_few_shot: 3
    metrics:
    - type: acc_norm
      value: 33.26
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=GalrionSoftworks/MagnusIntellectus-12B-v1
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MATH Lvl 5 (4-Shot)
      type: hendrycks/competition_math
      args:
        num_few_shot: 4
    metrics:
    - type: exact_match
      value: 5.14
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=GalrionSoftworks/MagnusIntellectus-12B-v1
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GPQA (0-shot)
      type: Idavidrein/gpqa
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 4.59
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=GalrionSoftworks/MagnusIntellectus-12B-v1
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MuSR (0-shot)
      type: TAUR-Lab/MuSR
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 15.18
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=GalrionSoftworks/MagnusIntellectus-12B-v1
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU-PRO (5-shot)
      type: TIGER-Lab/MMLU-Pro
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 26.9
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=GalrionSoftworks/MagnusIntellectus-12B-v1
      name: Open LLM Leaderboard
license: apache-2.0
pipeline_tag: text-generation
library_name: transformers
---

# MagnusIntellectus-12B-v1
![image/png](https://cdn-uploads.huggingface.co/production/uploads/66b564058d9afb7a9d5607d5/hUVJI1Qa4tCMrZWMgYkoD.png)

How pleasant, the rocks appear to have made a decent conglomerate. A-.

MagnusIntellectus is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [UsernameJustAnother/Nemo-12B-Marlin-v5](https://huggingface.co/UsernameJustAnother/Nemo-12B-Marlin-v5)
* [anthracite-org/magnum-12b-v2](https://huggingface.co/anthracite-org/magnum-12b-v2)


## 🧩 Configuration

```yaml
models:
  - model: UsernameJustAnother/Nemo-12B-Marlin-v5
    parameters:
      density: 0.4
      weight: 0.70
  - model: anthracite-org/magnum-12b-v2
    parameters:
      density: 0.6
      weight: 0.30

merge_method: ties
base_model: UsernameJustAnother/Nemo-12B-Marlin-v5
parameters:
  normalize: true
dtype: bfloat16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "GalrionSoftworks/MagnusIntellectus-12B-v1"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_GalrionSoftworks__MagnusIntellectus-12B-v1)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |21.55|
|IFEval (0-Shot)    |44.21|
|BBH (3-Shot)       |33.26|
|MATH Lvl 5 (4-Shot)| 5.14|
|GPQA (0-shot)      | 4.59|
|MuSR (0-shot)      |15.18|
|MMLU-PRO (5-shot)  |26.90|