license: apache-2.0
tags:
- moe
- merge
- mergekit
- Solar Moe
- Solar
- Umbra
model-index:
- name: Umbra-v2.1-MoE-4x10.7
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: 69.11
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Steelskull/Umbra-v2.1-MoE-4x10.7
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: 87.57
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Steelskull/Umbra-v2.1-MoE-4x10.7
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: 66.48
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Steelskull/Umbra-v2.1-MoE-4x10.7
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: 66.57
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Steelskull/Umbra-v2.1-MoE-4x10.7
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: 83.11
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Steelskull/Umbra-v2.1-MoE-4x10.7
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: 68.69
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Steelskull/Umbra-v2.1-MoE-4x10.7
name: Open LLM Leaderboard
Umbra-v2.1-MoE-4x10.7
The [Umbra Series] is an offshoot of the [Lumosia Series] With the goal to be a General assistant that has a knack for story telling and RP/ERP
-What's New in v2.1?
Umbra v2.1 isn't just a simple update; it's like giving the model a double shot of espresso. Ive changed the models and prompts, in an attempt to make Umbra not only your go-to assistant for general knowledge but also a great storyteller and RP/ERP companion.
-Longer Positive, Shorter Negative
In an effort to trick the gates into being less uptight, Ive added more positive prompts and snappier negative ones. These changes are based on the model's strengths and, frankly, my whimsical preferences.
-Experimental, As Always
Remember, folks, "v2.1" doesn't mean it's superior to its predecessors – it's just another step in the quest. It's the 'Empire Strikes Back' of our series – could be better, could be worse, but definitely more dramatic.
-Base Context and Coherence
Umbra v2.1 has a base context of 8k scrolling window.
-The Tavern Card
Just for fun - the Umbra Personality Tavern Card. It's your gateway to immersive storytelling experiences, a little like having a 'Choose Your Own Adventure' book, but way cooler because it's digital and doesn't get lost under your bed.
-Token Error? Fixed!
Umbra-v2 had a tokenizer error but was removed faster than you can say "Cops love Donuts"
So, give Umbra v2.1 a whirl and let me know how it goes. Your feedback is like the secret sauce in my development burger.
### System:
### USER:{prompt}
### Assistant:
Settings:
Temp: 1.0
min-p: 0.02-0.1
Evals:
- Avg: 73.59
- ARC: 69.11
- HellaSwag: 87.57
- MMLU: 66.48
- T-QA: 66.75
- Winogrande: 83.11
- GSM8K: 68.69
Examples:
posted soon
posted soon
🧩 Configuration
base_model: vicgalle/CarbonBeagle-11B
gate_mode: hidden
dtype: bfloat16
experts:
- source_model: vicgalle/CarbonBeagle-11B
positive_prompts: [Revamped]
- source_model: Sao10K/Fimbulvetr-10.7B-v1
positive_prompts: [Revamped]
- source_model: bn22/Nous-Hermes-2-SOLAR-10.7B-MISALIGNED
positive_prompts: [Revamped]
- source_model: Yhyu13/LMCocktail-10.7B-v1
positive_prompts: [Revamed]
Umbra-v2-MoE-4x10.7 is a Mixure of Experts (MoE) made with the following models:
* [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)
💻 Usage
!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"])
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 73.59 |
| AI2 Reasoning Challenge (25-Shot) | 69.11 |
| HellaSwag (10-Shot) | 87.57 |
| MMLU (5-Shot) | 66.48 |
| TruthfulQA (0-shot) | 66.57 |
| Winogrande (5-shot) | 83.11 |
| GSM8k (5-shot) | 68.69 |