solar_merge_test_2
๐งฉ Configuration
base_model: beomi/OPEN-SOLAR-KO-10.7B
dtype: float16
experts:
- source_model: beomi/OPEN-SOLAR-KO-10.7B
positive_prompts: ["๋น์ ์ ์น์ ํ ๋ณดํธ์ ์ธ ์ด์์คํดํธ์ด๋ค."]
- source_model: hyeogi/SOLAR-10.7B-dpo-v1
positive_prompts: ["๋น์ ์ ์น์ ํ ์ด์์คํดํธ์ด๋ค."]
- source_model: GAI-LLM/OPEN-SOLAR-KO-10.7B-mixed-v15
positive_prompts: ["๋น์ ์ ์น์ ํ ์ด์์คํดํธ์ด๋ค."]
- source_model: megastudyedu/M-SOLAR-10.7B-v1.1-beta
positive_prompts: ["๋น์ ์ ์น์ ํ ์ด์์คํดํธ์ด๋ค."]
gate_mode: cheap_embed
tokenizer_source: base
๐ป 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"])
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