README.md

---
license: apache-2.0
library_name: transformers
tags:
- mergekit
- merge
base_model: CultriX/NeuralTrix-7B-dpo
model-index:
- name: NeuralZephyr-Beagle-7B
 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: 68.6
 name: normalized accuracy
 source:
 url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/NeuralZephyr-Beagle-7B
 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: 86.38
 name: normalized accuracy
 source:
 url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/NeuralZephyr-Beagle-7B
 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: 64.67
 name: accuracy
 source:
 url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/NeuralZephyr-Beagle-7B
 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: 65.17
 source:
 url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/NeuralZephyr-Beagle-7B
 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: 81.14
 name: accuracy
 source:
 url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/NeuralZephyr-Beagle-7B
 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: 63.46
 name: accuracy
 source:
 url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/NeuralZephyr-Beagle-7B
 name: Open LLM Leaderboard
---

![logo](thumbn.png)

# merge

This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

Code credit: [this excellent medium blog](https://medium.com/towards-data-science/merge-large-language-models-with-mergekit-2118fb392b54)

## Merge Details
### Merge Method

This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using CultriX/NeuralTrix-7B-dpo as a base.

### Models Merged

The following models were included in the merge:
* mlabonne/NeuralBeagle14-7B
* HuggingFaceH4/zephyr-7b-alpha

### Benchmarks

#### Open LLM Leaderboard 
| Model | Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K |
| ------------------------------ | ------- | ---- | --------- | ----- | ---------- | ---------- | ----- |
| mayacinka/NeuralZephyr-Beagle-7B | 71.57 | 68.6 | 86.38 | 64.67 | 65.17 | 81.14 | 63.46 |


### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
 - model: CultriX/NeuralTrix-7B-dpo
 - model: HuggingFaceH4/zephyr-7b-alpha
 parameters:
 density: 0.83
 weight: 0.4
 - model: mlabonne/NeuralBeagle14-7B
 parameters: 
 density: 0.83
 weight: 0.6
merge_method: dare_ties
base_model: CultriX/NeuralTrix-7B-dpo
parameters:
 int8_mask: true
dtype: bfloat16
```

# Inference 

```python
# pip install transformers

from transformers import AutoTokenizer
import transformers
import torch

model = "mayacinka/NeuralZephyr-Beagle-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"])
```
# [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_mayacinka__NeuralZephyr-Beagle-7B)

| Metric |Value|
|---------------------------------|----:|
|Avg. |71.57|
|AI2 Reasoning Challenge (25-Shot)|68.60|
|HellaSwag (10-Shot) |86.38|
|MMLU (5-Shot) |64.67|
|TruthfulQA (0-shot) |65.17|
|Winogrande (5-shot) |81.14|
|GSM8k (5-shot) |63.46|