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---
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- abideen/MonarchCoder-7B
- eldogbbhed/NeuralPearlBeagle
base_model:
- abideen/MonarchCoder-7B
- eldogbbhed/NeuralPearlBeagle
model-index:
- name: NeuralMonarchCoderPearlBeagle
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 68.52
name: normalized accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=eldogbbhed/NeuralMonarchCoderPearlBeagle
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm
value: 87.22
name: normalized accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=eldogbbhed/NeuralMonarchCoderPearlBeagle
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 64.53
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=eldogbbhed/NeuralMonarchCoderPearlBeagle
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2
value: 61.19
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=eldogbbhed/NeuralMonarchCoderPearlBeagle
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc
value: 80.51
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=eldogbbhed/NeuralMonarchCoderPearlBeagle
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 67.02
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=eldogbbhed/NeuralMonarchCoderPearlBeagle
name: Open LLM Leaderboard
---
<center><img src='https://i.postimg.cc/K8N1SLYx/ee68f836-5714-4d6f-9646-22f0f7f1601e.png' width='1360px' height='768'></center>
# NeuralMonarchCoderPearlBeagle
NeuralMonarchCoderPearlBeagle is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [abideen/MonarchCoder-7B](https://huggingface.co./abideen/MonarchCoder-7B)
* [eldogbbhed/NeuralPearlBeagle](https://huggingface.co./eldogbbhed/NeuralPearlBeagle)
### Goals
This is a TIES merge, formed from MonarchCoder-7b (A merge of Alpha Monarch and TessCoder) and NeuralPearlBeagle(which is a merge of mlabonne's NeuralBeagle14-7b and Pearl-7B-Slerp).
It is a somewhat haphazard experiment to see if we can merge more math and coding capabilities into the already outstanding NeuralBeagle14-7b and still maintain the same positive chat abilities.
## 🧩 Configuration
```yaml
models:
- model: abideen/MonarchCoder-7B
parameters:
density: 0.6
weight: 0.5
- model: eldogbbhed/NeuralPearlBeagle
parameters:
density: 0.8
weight: 0.8
merge_method: ties
base_model: eldogbbhed/NeuralPearlBeagle
parameters:
normalize: true
int8_mask: true
dtype: float16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "eldogbbhed/NeuralMonarchCoderPearlBeagle"
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/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/details_eldogbbhed__NeuralMonarchCoderPearlBeagle)
| Metric |Value|
|---------------------------------|----:|
|Avg. |71.50|
|AI2 Reasoning Challenge (25-Shot)|68.52|
|HellaSwag (10-Shot) |87.22|
|MMLU (5-Shot) |64.53|
|TruthfulQA (0-shot) |61.19|
|Winogrande (5-shot) |80.51|
|GSM8k (5-shot) |67.02|
|