liminerity / Blur-4x7b-MOE-v0.1

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Total runs: 25
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Model's Last Updated: March 12 2024
text-generation

Introduction of Blur-4x7b-MOE-v0.1

Model Details of Blur-4x7b-MOE-v0.1

Blur-4x7b-MOE-v0.1

Blur-4x7b-MOE-v0.1 is a Mixure of Experts (MoE) made with the following models using LazyMergekit :

🧩 Configuration
base_model: 222gate/BrurryDog-7b-v0.1
gate_mode: hidden
dtype: bfloat16
experts:
  - source_model: 222gate/Blurdus-7b-v0.1
    positive_prompts:
    - "versatile"
    - "helpful"
    - "factual"
    - "integrated"
    - "adaptive"
    - "comprehensive"
    - "balanced"
    negative_prompts:
    - "specialized"
    - "narrow"
    - "focused"
    - "limited"
    - "specific"

  - source_model: 222gate/Blurred-Beagle-7b-slerp
    positive_prompts:
    - "creative"
    - "chat"
    - "discuss"
    - "culture"
    - "world"
    - "expressive"
    - "detailed"
    - "imaginative"
    - "engaging"
    negative_prompts:
    - "sorry"
    - "cannot"
    - "factual"
    - "concise"
    - "straightforward"
    - "objective"
    - "dry"

  - source_model: liminerity/Blur-7b-v1.21
    positive_prompts:
    - "analytical"
    - "accurate"
    - "logical"
    - "knowledgeable"
    - "precise"
    - "calculate"
    - "compute"
    - "solve"
    - "work"
    - "python"
    - "javascript"
    - "programming"
    - "algorithm"
    - "tell me"
    - "assistant"
    negative_prompts:
    - "creative"
    - "abstract"
    - "imaginative"
    - "artistic"
    - "emotional"
    - "mistake"
    - "inaccurate"

  - source_model: liminerity/Blur-7B-slerp-v0.1
    positive_prompts:
    - "instructive"
    - "clear"
    - "directive"
    - "helpful"
    - "informative"
    negative_prompts:
    - "exploratory"
    - "open-ended"
    - "narrative"
    - "speculative"
    - "artistic"
💻 Usage
!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "222gate/Blur-4x7b-MOE-v0.1"

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. 74.29
AI2 Reasoning Challenge (25-Shot) 72.27
HellaSwag (10-Shot) 88.14
MMLU (5-Shot) 65.05
TruthfulQA (0-shot) 68.82
Winogrande (5-shot) 82.56
GSM8k (5-shot) 68.92

Runs of liminerity Blur-4x7b-MOE-v0.1 on huggingface.co

25
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0
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1
3-day runs
0
7-day runs
3
30-day runs

More Information About Blur-4x7b-MOE-v0.1 huggingface.co Model

More Blur-4x7b-MOE-v0.1 license Visit here:

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Blur-4x7b-MOE-v0.1 install

Blur-4x7b-MOE-v0.1 is an open source model from GitHub that offers a free installation service, and any user can find Blur-4x7b-MOE-v0.1 on GitHub to install. At the same time, huggingface.co provides the effect of Blur-4x7b-MOE-v0.1 install, users can directly use Blur-4x7b-MOE-v0.1 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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