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---
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- Kukedlc/Neural-Cosmic-7B-slerp
- Kukedlc/NeuralLogic-7B-V
- Kukedlc/SuperCombo
base_model:
- Kukedlc/Neural-Cosmic-7B-slerp
- Kukedlc/NeuralLogic-7B-V
- Kukedlc/SuperCombo
model-index:
- name: Neural-Cosmic-Boy-7B-slerp
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: 70.48
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Kukedlc/Neural-Cosmic-Boy-7B-slerp
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: 87.65
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Kukedlc/Neural-Cosmic-Boy-7B-slerp
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: 64.92
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Kukedlc/Neural-Cosmic-Boy-7B-slerp
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: 67.1
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Kukedlc/Neural-Cosmic-Boy-7B-slerp
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: 82.0
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Kukedlc/Neural-Cosmic-Boy-7B-slerp
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: 72.33
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Kukedlc/Neural-Cosmic-Boy-7B-slerp
name: Open LLM Leaderboard
---
## Note: The merge method is ties, not slerp.
# Neural-Cosmic-Boy-7B-slerp
![Neural Cosmic Boy - 7 billons params](https://raw.githubusercontent.com/kukedlc87/imagenes/main/DALL%C2%B7E%202024-02-17%2020.28.38%20-%20Visualize%20a%20human%20face%20composed%20entirely%20of%20topographic%20lines%2C%20similar%20to%20those%20found%20on%20a%20mountain%20map.%20This%20artistic%20representation%20uses%20only%20lines%20.webp)
Neural-Cosmic-Boy-7B-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Kukedlc/Neural-Cosmic-7B-slerp](https://huggingface.co/Kukedlc/Neural-Cosmic-7B-slerp)
* [Kukedlc/NeuralLogic-7B-V](https://huggingface.co/Kukedlc/NeuralLogic-7B-V)
* [Kukedlc/SuperCombo](https://huggingface.co/Kukedlc/SuperCombo)
## 🧩 Configuration
```yaml
models:
- model: Kukedlc/Neural-Cosmic-7B-slerp
parameters:
density: [1, 0.7, 0.1] # density gradient
weight: 1.0
- model: Kukedlc/NeuralLogic-7B-V
parameters:
density: 0.5
weight: [0, 0.3, 0.7, 1] # weight gradient
- model: Kukedlc/SuperCombo
parameters:
density: 0.33
weight:
- filter: mlp
value: 0.5
- value: 0
merge_method: ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
normalize: true
int8_mask: true
dtype: float16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Kukedlc/Neural-Cosmic-Boy-7B-slerp"
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_Kukedlc__Neural-Cosmic-Boy-7B-slerp)
| Metric |Value|
|---------------------------------|----:|
|Avg. |74.08|
|AI2 Reasoning Challenge (25-Shot)|70.48|
|HellaSwag (10-Shot) |87.65|
|MMLU (5-Shot) |64.92|
|TruthfulQA (0-shot) |67.10|
|Winogrande (5-shot) |82.00|
|GSM8k (5-shot) |72.33|