MoEnsterBeagle

MoEnsterBeagle

MoEnsterBeagle is a Mixture of Experts (MoE) made with the following models using LazyMergekit:

• mlabonne/NeuralBeagle14-7B
• timpal0l/Mistral-7B-v0.1-flashback-v2
• Nexusflow/Starling-LM-7B-beta
• AI-Sweden-Models/tyr

🧩 Configuration

base_model: mlabonne/NeuralBeagle14-7B
gate_mode: cheap_embed
experts:
  - source_model: mlabonne/NeuralBeagle14-7B
    positive_prompts:
    - "chat"
    - "assistant"
    - "explain"
    - "tell me"
    - "english"
  - source_model: timpal0l/Mistral-7B-v0.1-flashback-v2
    positive_prompts:
    - "förklara"
    - "sammanfatta"
    - "svenska"
  - source_model: Nexusflow/Starling-LM-7B-beta
    positive_prompts: 
    - "code"
    - "programming"
    - "algorithm"
  - source_model: AI-Sweden-Models/tyr
    positive_prompts: 
    - "varför"
    - "förenkla"
    - "lagen"

💻 Usage

!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "FredrikBL/MoEnsterBeagle"

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"])