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---
license: apache-2.0
tags:
- moe
- merge
- mergekit
- vicgalle/CarbonBeagle-11B
- Sao10K/Fimbulvetr-10.7B-v1
- bn22/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED
- Yhyu13/LMCocktail-10.7B-v1
---
# Umbra-v2-MoE-4x10.7
Umbra-v2-MoE-4x10.7 is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [vicgalle/CarbonBeagle-11B](https://huggingface.co./vicgalle/CarbonBeagle-11B)
* [Sao10K/Fimbulvetr-10.7B-v1](https://huggingface.co./Sao10K/Fimbulvetr-10.7B-v1)
* [bn22/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED](https://huggingface.co./bn22/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED)
* [Yhyu13/LMCocktail-10.7B-v1](https://huggingface.co./Yhyu13/LMCocktail-10.7B-v1)
## 🧩 Configuration
```yamlbase_model: vicgalle/CarbonBeagle-11B
gate_mode: hidden
dtype: bfloat16
experts:
- source_model: vicgalle/CarbonBeagle-11B
positive_prompts:
- "versatile"
- "adaptive"
- "comprehensive"
- "integrated"
- "balanced"
- "all-rounder"
- "flexible"
- "wide-ranging"
- "multi-disciplinary"
- "holistic"
- "innovative"
- "eclectic"
- "resourceful"
- "dynamic"
- "robust"
negative_prompts:
- "narrow"
- "specialized"
- "limited"
- "focused"
- source_model: Sao10K/Fimbulvetr-10.7B-v1
positive_prompts:
- "creative"
- "storytelling"
- "expressive"
- "imaginative"
- "engaging"
- "verbose"
- "narrative"
- "descriptive"
- "elaborate"
- "fictional"
- "artistic"
- "vivid"
- "colorful"
- "fantastical"
- "lyrical"
negative_prompts:
- "sorry"
- "I cannot"
- "factual"
- "concise"
- "straightforward"
- "objective"
- "dry"
- source_model: bn22/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED
positive_prompts:
- "intelligent"
- "analytical"
- "accurate"
- "knowledgeable"
- "logical"
- "data-driven"
- "scientific"
- "rational"
- "precise"
- "methodical"
- "empirical"
- "systematic"
- "efficient"
- "scholarly"
- "statistical"
- "calculate"
- "compute"
- "solve"
- "work"
- "python"
- "javascript"
- "programming"
- "algorithm"
- "tell me"
- "assistant"
negative_prompts:
- "creative"
- "imaginative"
- "abstract"
- "emotional"
- "artistic"
- "speculative"
- source_model: Yhyu13/LMCocktail-10.7B-v1
positive_prompts:
- "instructive"
- "verbose"
- "descriptive"
- "clear"
- "detailed"
- "informative"
- "explanatory"
- "elucidative"
- "articulate"
- "comprehensive"
- "educational"
- "thorough"
- "specific"
- "clarifying"
- "structured"
negative_prompts:
- "concise"
- "vague"```
## 💻 Usage
```python
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Steelskull/Umbra-v2-MoE-4x10.7"
tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
"text-generation",
model=model,
model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
)
messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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"])
``` |