ramonda-monarch-7b / README.md
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---
tags:
- merge
- mergekit
- lazymergekit
- eren23/ogno-monarch-jaskier-merge-7b
- liminerity/Omningotex-7b-slerp
- yleo/OgnoMonarch-7B
base_model:
- eren23/ogno-monarch-jaskier-merge-7b
---
# ramonda-monarch-7b
ramonda-monarch-7b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [eren23/ogno-monarch-jaskier-merge-7b](https://huggingface.co./eren23/ogno-monarch-jaskier-merge-7b)
* [liminerity/Omningotex-7b-slerp](https://huggingface.co./liminerity/Omningotex-7b-slerp)
* [yleo/OgnoMonarch-7B](https://huggingface.co./yleo/OgnoMonarch-7B)
# 🏆 Benchmarks
### Open LLM Leaderboard
| Model | Average | ARC_easy | HellaSwag | MMLU | TruthfulQA-mc2 | Winogrande | GSM8K | ARC_challenge |
|------------------------|--------:|-----:|----------:|-----:|-----------:|-----------:|------:|--------:|
| mayacinka/ramonda-monarch-7b | 76.66 | 86.91 | 87.45 | 61.97 | 77.4 | 81.61 | 73.01 | 68.26 |
### MMLU
| Groups |Version|Filter|n-shot|Metric|Value | |Stderr|
|------------------|-------|------|------|------|-----:|---|-----:|
|mmlu |N/A |none | 0|acc |0.6197|± |0.0039|
| - humanities |N/A |none |None |acc |0.5762|± |0.0067|
| - other |N/A |none |None |acc |0.6936|± |0.0080|
| - social_sciences|N/A |none |None |acc |0.7192|± |0.0079|
| - stem |N/A |none |None |acc |0.5147|± |0.0085|
### Nous benchmark
[autoEval](https://gist.github.com/majacinka/51d302a6413a1f145f77f492c7b47c04)
| Model | AGIEval | GPT4All | TruthfulQA | Bigbench | Average |
|---------------------|---------|---------|------------|----------|---------|
| mayacinka/ramonda-monarch-7b | 44.63 | 77.41 | 77.41 | 49.59 | 62.26 |
## 🧩 Configuration
```yaml
models:
- model: bardsai/jaskier-7b-dpo-v5.6
# No parameters necessary for base model
- model: eren23/ogno-monarch-jaskier-merge-7b
parameters:
density: 0.53
weight: 0.4
- model: liminerity/Omningotex-7b-slerp
parameters:
density: 0.53
weight: 0.3
- model: yleo/OgnoMonarch-7B
parameters:
density: 0.53
weight: 0.3
merge_method: dare_ties
base_model: bardsai/jaskier-7b-dpo-v5.6
parameters:
int8_mask: true
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "mayacinka/ramonda-monarch-7b"
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"])
```