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1base_model: allknowingroger/MultiverseEx26-7B-slerp
2experts:
3 - source_model: allknowingroger/MultiverseEx26-7B-slerp
4 positive_prompts: ["what"]
5 - source_model: allknowingroger/Neurallaymons-7B-slerp
6 positive_prompts: ["math"]1!pip install -qU transformers bitsandbytes accelerate
2
3from transformers import AutoTokenizer
4import transformers
5import torch
6
7model = "allknowingroger/MultiverseEx26-Neurallaymons-12B-MoE"
8
9tokenizer = AutoTokenizer.from_pretrained(model)
10pipeline = transformers.pipeline(
11 "text-generation",
12 model=model,
13 model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
14)
15
16messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
17prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
18outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
19print(outputs[0]["generated_text"])