metadata

license: apache-2.0
tags:
  - moe
  - frankenmoe
  - merge
  - mergekit
  - lazymergekit
  - beomi/OPEN-SOLAR-KO-10.7B
  - hyeogi/SOLAR-10.7B-dpo-v1
  - GAI-LLM/OPEN-SOLAR-KO-10.7B-mixed-v15
  - megastudyedu/M-SOLAR-10.7B-v1.1-beta
base_model:
  - beomi/OPEN-SOLAR-KO-10.7B
  - hyeogi/SOLAR-10.7B-dpo
  - GAI-LLM/OPEN-SOLAR-KO-10.7B-mixed-v15
  - megastudyedu/M-SOLAR-10.7B-v1.1-beta

solar_merge_test_2

🧩 Configuration

base_model: beomi/OPEN-SOLAR-KO-10.7B
dtype: float16
experts:
  - source_model: beomi/OPEN-SOLAR-KO-10.7B
    positive_prompts: ["당신은 친절한 보편적인 어시스턴트이다."]
  - source_model: hyeogi/SOLAR-10.7B-dpo-v1
    positive_prompts: ["당신은 친절한 어시스턴트이다."]
  - source_model: GAI-LLM/OPEN-SOLAR-KO-10.7B-mixed-v15
    positive_prompts: ["당신은 친절한 어시스턴트이다."]
  - source_model: megastudyedu/M-SOLAR-10.7B-v1.1-beta
    positive_prompts: ["당신은 친절한 어시스턴트이다."]
gate_mode: cheap_embed
tokenizer_source: base

💻 Usage

!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "jieunhan/solar_merge_test_2"

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"])