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---
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- Kukedlc/NeuralKrishna-7B-v3
- Kukedlc/NeuralMarioMonarch-7B-slerp
- liminerity/M7-7b
base_model:
- Kukedlc/NeuralKrishna-7B-v3
- Kukedlc/NeuralMarioMonarch-7B-slerp
- liminerity/M7-7b
model-index:
- name: NeuralSirKrishna-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: 73.72
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Kukedlc/NeuralSirKrishna-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: 89.05
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Kukedlc/NeuralSirKrishna-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: 64.63
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Kukedlc/NeuralSirKrishna-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: 75.6
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Kukedlc/NeuralSirKrishna-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: 85.32
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Kukedlc/NeuralSirKrishna-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: 71.27
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Kukedlc/NeuralSirKrishna-7b
name: Open LLM Leaderboard
---
<div align="center" style="font-size: 44px;">🧞 NeuralSirKrishna-7b</div>
## 👩💻 Try here!
[Talking to Sir Neural Krishna 7b](https://huggingface.co/spaces/Kukedlc/Neural-Sir-Krishna-7b-GGUF)
NeuralKrishna-7B-v4 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Kukedlc/NeuralKrishna-7B-v3](https://huggingface.co/Kukedlc/NeuralKrishna-7B-v3)
* [Kukedlc/NeuralMarioMonarch-7B-slerp](https://huggingface.co/Kukedlc/NeuralMarioMonarch-7B-slerp)
* [liminerity/M7-7b](https://huggingface.co/liminerity/M7-7b)
# Chat
- User: Create an advanced theory about the origin of life on earth that is new, innovative, and disruptive, totally new with no resemblance to anything else but at the same time that can be real.
- System: I. The Symbiotic Cosmic Initiation Hypothesis (SCIH)
To propose a groundbreaking and disruptive theory about the origin of life on Earth, let's envision an interconnected web of cosmic events that transcends conventional understanding. The Symbiotic Cosmic Initiation Hypothesis (SCIH) posits that life didn't arise from a singular event or molecular accident but rather from a complex, multifaceted interplay between extraterrestrial entities and our planet's nascent environment. Here are its core tenets:
1. Prebiotic Symbionts: SCIH rejects the notion of a solitary "building block" or "spark of life." Instead, it postulates that prebiotic symbionts – self-replicating, organic-inorganic complexes – arrived on Earth from space via meteorites and comets. These symbionts, composed of a diverse array of biomolecules and mineral catalysts, were the products of extraterrestrial ecosystems or "astrobiomes."
2. Astrobiome Cross-Fertilization: The constant exchange of matter between our solar system's planets and asteroid belts facilitated the transfer of these prebiotic symbionts across vast distances. This cosmic symbiosis allowed for the intermingling of genetic and catalytic material, fostering evolutionary innovation and adaptability among these extraterrestrial life-forms.
3. Terrestrial Integration and Adaptation: Upon impacting Earth's surface, these prebiotic symbionts began to integrate with our planet's pre-existing chemical milieu. The resulting synergy between Earth-born and extraterrestrial biomolecules accelerated the formation of more complex organic structures, eventually leading to protocells – rudimentary, self-enclosed systems capable of rudimentary metabolism and replication.
4. The Catalytic Gaian Boost: As Earth's early atmosphere evolved to become more hospitable to life, a positive feedback loop between these protocells and our planet's environment ensued. The emergence of photosynthesis and other metabolic processes contributed to the creation of a self-regulating, life-nurturing environment – what we now call the Ga
## 🧩 Configuration
```yaml
models:
- model: Kukedlc/NeuralKrishna-7B-v3
# no parameters necessary for base model
- model: Kukedlc/NeuralKrishna-7B-v3
parameters:
density: 0.65
weight: 0.36
- model: Kukedlc/NeuralMarioMonarch-7B-slerp
parameters:
density: 0.6
weight: 0.34
- model: liminerity/M7-7b
parameters:
density: 0.4
weight: 0.3
merge_method: dare_ties
base_model: Kukedlc/NeuralKrishna-7B-v3
parameters:
int8_mask: true
dtype: bfloat16
random_seed: 0
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Kukedlc/NeuralSirKrishna-7b"
messages = [{"role": "user", "content": """Create an advanced theory about the origin of life on earth that is new,
innovative, and disruptive, totally new with no resemblance to anything else but at the same time that can be real."""}]
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"])
```
# 🍃 Family models:
# [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__NeuralSirKrishna-7b)
| Metric |Value|
|---------------------------------|----:|
|Avg. |76.60|
|AI2 Reasoning Challenge (25-Shot)|73.72|
|HellaSwag (10-Shot) |89.05|
|MMLU (5-Shot) |64.63|
|TruthfulQA (0-shot) |75.60|
|Winogrande (5-shot) |85.32|
|GSM8k (5-shot) |71.27|
|